{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/image-super-resolution/papers/ran/2","list_of":"/task/image-super-resolution","task":"Image Super-Resolution","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":2,"pages_in_order":2,"rows_per_page":100,"rows":[101,188],"of":188,"counts":{"archive_papers_tagged":1589,"with_a_code_link":783,"where_syntology_ran_a_sample":188,"not_listed_spam_title":0,"listed":1589,"listed_where_code_ran":188,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":171,"every_run_a_failure_of_syntologys_instrument":17,"listed_with_a_run_with_no_instrument_failure":171,"listed_every_run_a_failure_of_syntologys_instrument":17,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/image-super-resolution/papers/ran/1","prev":"/task/image-super-resolution/papers/ran/1","next":null,"papers":[{"url":"/paper/ntire-2022-challenge-on-efficient-super","slug":"ntire-2022-challenge-on-efficient-super","title":"NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results","date":"2022-05-11","arxiv_id":"2205.05675","repositories_listed":2,"syntology":{"n":12,"n_ran":8,"n_constructed":0,"n_ran_checked":5,"n_instrument":3,"n_unverified":4,"n_honours":0,"n_violates":1,"n_no_contract":4,"n_pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 1 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/ntire-2022-challenge-on-efficient-super#ran","syntology_url":"https://syntology.ai/paper/2205.05675","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.05675"}},"official":{"repos":["ofsoundof/imdn","ofsoundof/ntire2022_esr"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/dual-adversarial-adaptation-for-cross-device","slug":"dual-adversarial-adaptation-for-cross-device","title":"Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution","date":"2022-05-07","arxiv_id":"2205.03524","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":4,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":6,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dual-adversarial-adaptation-for-cross-device#ran","syntology_url":"https://syntology.ai/paper/2205.03524","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.03524"}},"official":{"repos":["lonelyhope/dada"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/fast-and-memory-efficient-network-towards","slug":"fast-and-memory-efficient-network-towards","title":"Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution","date":"2022-04-18","arxiv_id":"2204.08397","repositories_listed":2,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":4,"n_instrument":3,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/fast-and-memory-efficient-network-towards#ran","syntology_url":"https://syntology.ai/paper/2204.08397","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.08397"}},"official":{"repos":["nju-jet/fmen"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/efficient-and-degradation-adaptive-network","slug":"efficient-and-degradation-adaptive-network","title":"Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution","date":"2022-03-27","arxiv_id":"2203.14216","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/efficient-and-degradation-adaptive-network#ran","syntology_url":"https://syntology.ai/paper/2203.14216","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.14216"}},"official":{"repos":["csjliang/dasr"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptive-patch-exiting-for-scalable-single","slug":"adaptive-patch-exiting-for-scalable-single","title":"Adaptive Patch Exiting for Scalable Single Image Super-Resolution","date":"2022-03-22","arxiv_id":"2203.11589","repositories_listed":1,"syntology":{"n":13,"n_ran":6,"n_constructed":3,"n_ran_checked":3,"n_instrument":3,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":13,"phrase":"6 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/adaptive-patch-exiting-for-scalable-single#ran","syntology_url":"https://syntology.ai/paper/2203.11589","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.11589"}},"official":{"repos":["littlepure2333/ape"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":7,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/arm-any-time-super-resolution-method","slug":"arm-any-time-super-resolution-method","title":"ARM: Any-Time Super-Resolution Method","date":"2022-03-21","arxiv_id":"2203.10812","repositories_listed":1,"syntology":{"n":8,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":8,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/arm-any-time-super-resolution-method#ran","syntology_url":"https://syntology.ai/paper/2203.10812","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10812"}},"official":{"repos":["chenbong/arm-net"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/details-or-artifacts-a-locally-discriminative","slug":"details-or-artifacts-a-locally-discriminative","title":"Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution","date":"2022-03-17","arxiv_id":"2203.09195","repositories_listed":2,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/details-or-artifacts-a-locally-discriminative#ran","syntology_url":"https://syntology.ai/paper/2203.09195","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09195"}},"official":{"repos":["csjliang/ldl"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/a-text-attention-network-for-spatial","slug":"a-text-attention-network-for-spatial","title":"A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution","date":"2022-03-17","arxiv_id":"2203.09388","repositories_listed":2,"syntology":{"n":25,"n_ran":18,"n_constructed":4,"n_ran_checked":14,"n_instrument":4,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"18 ran (of which 4 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 4 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/a-text-attention-network-for-spatial#ran","syntology_url":"https://syntology.ai/paper/2203.09388","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09388"}},"official":{"repos":["mjq11302010044/tatt"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/gcfsr-a-generative-and-controllable-face","slug":"gcfsr-a-generative-and-controllable-face","title":"GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors","date":"2022-03-14","arxiv_id":"2203.07319","repositories_listed":0,"syntology":{"n":20,"n_ran":11,"n_constructed":8,"n_ran_checked":10,"n_instrument":1,"n_unverified":9,"n_honours":0,"n_violates":1,"n_no_contract":9,"n_pointer_only":20,"phrase":"11 ran (of which 8 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 1 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/gcfsr-a-generative-and-controllable-face#ran","syntology_url":"https://syntology.ai/paper/2203.07319","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07319"}},"official":null}},{"url":"/paper/efficient-long-range-attention-network-for","slug":"efficient-long-range-attention-network-for","title":"Efficient Long-Range Attention Network for Image Super-resolution","date":"2022-03-13","arxiv_id":"2203.06697","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":6,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 6 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified; every one of the 6 samples that ran constructed an object rather than computing a result","sample_list":"/paper/efficient-long-range-attention-network-for#ran","syntology_url":"https://syntology.ai/paper/2203.06697","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.06697"}},"official":{"repos":["xindongzhang/elan"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":6,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/unfolded-deep-kernel-estimation-for-blind","slug":"unfolded-deep-kernel-estimation-for-blind","title":"Unfolded Deep Kernel Estimation for Blind Image Super-resolution","date":"2022-03-10","arxiv_id":"2203.05568","repositories_listed":1,"syntology":{"n":17,"n_ran":12,"n_constructed":9,"n_ran_checked":9,"n_instrument":3,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":17,"phrase":"12 ran (of which 9 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 3 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/unfolded-deep-kernel-estimation-for-blind#ran","syntology_url":"https://syntology.ai/paper/2203.05568","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.05568"}},"official":{"repos":["natezhenghy/udke"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":9,"n_ran_no_instrument_failure":9,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptive-cross-layer-attention-for-image-1","slug":"adaptive-cross-layer-attention-for-image-1","title":"Adaptive Cross-Layer Attention for Image Restoration","date":"2022-03-04","arxiv_id":"2203.03619","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adaptive-cross-layer-attention-for-image-1#ran","syntology_url":"https://syntology.ai/paper/2203.03619","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.03619"}},"official":{"repos":["sdl-asu/acla"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/conditional-simulation-using-diffusion","slug":"conditional-simulation-using-diffusion","title":"Conditional Simulation Using Diffusion Schrödinger Bridges","date":"2022-02-27","arxiv_id":"2202.13460","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/conditional-simulation-using-diffusion#ran","syntology_url":"https://syntology.ai/paper/2202.13460","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.13460"}},"official":{"repos":["vdeborto/cdsb"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/efficient-non-local-contrastive-attention-for","slug":"efficient-non-local-contrastive-attention-for","title":"Efficient Non-Local Contrastive Attention for Image Super-Resolution","date":"2022-01-11","arxiv_id":"2201.03794","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":1,"n_ran_checked":3,"n_instrument":3,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":1,"n_pointer_only":6,"phrase":"6 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 0 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/efficient-non-local-contrastive-attention-for#ran","syntology_url":"https://syntology.ai/paper/2201.03794","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.03794"}},"official":{"repos":["zj-binxia/enlca"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":1,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/detail-preserving-transformer-for-light-field","slug":"detail-preserving-transformer-for-light-field","title":"Detail-Preserving Transformer for Light Field Image Super-Resolution","date":"2022-01-02","arxiv_id":"2201.00346","repositories_listed":1,"syntology":{"n":21,"n_ran":10,"n_constructed":0,"n_ran_checked":6,"n_instrument":4,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":21,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 4 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/detail-preserving-transformer-for-light-field#ran","syntology_url":"https://syntology.ai/paper/2201.00346","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.00346"}},"official":{"repos":["bitszwang/dpt"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":11,"ran_from_kinds":["official"]}}},{"url":"/paper/text-gestalt-stroke-aware-scene-text-image","slug":"text-gestalt-stroke-aware-scene-text-image","title":"Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution","date":"2021-12-13","arxiv_id":"2112.08171","repositories_listed":2,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/text-gestalt-stroke-aware-scene-text-image#ran","syntology_url":"https://syntology.ai/paper/2112.08171","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.08171"}},"official":{"repos":["fudanvi/fudanocr"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/local-texture-estimator-for-implicit","slug":"local-texture-estimator-for-implicit","title":"Local Texture Estimator for Implicit Representation Function","date":"2021-11-17","arxiv_id":"2111.08918","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":3,"n_instrument":4,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":4,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/local-texture-estimator-for-implicit#ran","syntology_url":"https://syntology.ai/paper/2111.08918","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.08918"}},"official":{"repos":["jaewon-lee-b/lte"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/rbsricnn-raw-burst-super-resolution-through","slug":"rbsricnn-raw-burst-super-resolution-through","title":"RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network","date":"2021-10-25","arxiv_id":"2110.13217","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/rbsricnn-raw-burst-super-resolution-through#ran","syntology_url":"https://syntology.ai/paper/2110.13217","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.13217"}},"official":{"repos":["raoumer/rbsricnn"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/efficient-transformer-for-single-image-super","slug":"efficient-transformer-for-single-image-super","title":"Transformer for Single Image Super-Resolution","date":"2021-08-25","arxiv_id":"2108.11084","repositories_listed":1,"syntology":{"n":10,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":4,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/efficient-transformer-for-single-image-super#ran","syntology_url":"https://syntology.ai/paper/2108.11084","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.11084"}},"official":{"repos":["luissen/esrt"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/swinir-image-restoration-using-swin","slug":"swinir-image-restoration-using-swin","title":"SwinIR: Image Restoration Using Swin Transformer","date":"2021-08-23","arxiv_id":"2108.10257","repositories_listed":9,"syntology":{"n":45,"n_ran":30,"n_constructed":14,"n_ran_checked":16,"n_instrument":14,"n_unverified":15,"n_honours":0,"n_violates":0,"n_no_contract":16,"n_pointer_only":5,"phrase":"30 ran (of which 14 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 14 where Syntology's instrument failed) · 15 unverified","sample_list":"/paper/swinir-image-restoration-using-swin#ran","syntology_url":"https://syntology.ai/paper/2108.10257","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.10257"}},"official":{"repos":["jingyunliang/swinir"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/hierarchical-conditional-flow-a-unified","slug":"hierarchical-conditional-flow-a-unified","title":"Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling","date":"2021-08-11","arxiv_id":"2108.05301","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":2,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/hierarchical-conditional-flow-a-unified#ran","syntology_url":"https://syntology.ai/paper/2108.05301","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05301"}},"official":{"repos":["jingyunliang/hcflow"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mutual-affine-network-for-spatially-variant","slug":"mutual-affine-network-for-spatially-variant","title":"Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution","date":"2021-08-11","arxiv_id":"2108.05302","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":3,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/mutual-affine-network-for-spatially-variant#ran","syntology_url":"https://syntology.ai/paper/2108.05302","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05302"}},"official":{"repos":["jingyunliang/manet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/text-prior-guided-scene-text-image-super","slug":"text-prior-guided-scene-text-image-super","title":"Text Prior Guided Scene Text Image Super-resolution","date":"2021-06-29","arxiv_id":"2106.15368","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/text-prior-guided-scene-text-image-super#ran","syntology_url":"https://syntology.ai/paper/2106.15368","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.15368"}},"official":{"repos":["mjq11302010044/TPGSR"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/distilling-the-knowledge-from-normalizing","slug":"distilling-the-knowledge-from-normalizing","title":"Distilling the Knowledge from Conditional Normalizing Flows","date":"2021-06-24","arxiv_id":"2106.12699","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":5,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/distilling-the-knowledge-from-normalizing#ran","syntology_url":"https://syntology.ai/paper/2106.12699","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.12699"}},"official":{"repos":["yandex-research/distill-nf"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/fairness-for-image-generation-with-uncertain","slug":"fairness-for-image-generation-with-uncertain","title":"Fairness for Image Generation with Uncertain Sensitive Attributes","date":"2021-06-23","arxiv_id":"2106.12182","repositories_listed":1,"syntology":{"n":12,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":1,"n_no_contract":7,"n_pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/fairness-for-image-generation-with-uncertain#ran","syntology_url":"https://syntology.ai/paper/2106.12182","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.12182"}},"official":{"repos":["ajiljalal/code-cs-fairness"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/masa-sr-matching-acceleration-and-spatial","slug":"masa-sr-matching-acceleration-and-spatial","title":"MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution","date":"2021-06-04","arxiv_id":"2106.02299","repositories_listed":2,"syntology":{"n":7,"n_ran":6,"n_constructed":5,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"6 ran (of which 5 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/masa-sr-matching-acceleration-and-spatial#ran","syntology_url":"https://syntology.ai/paper/2106.02299","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.02299"}},"official":{"repos":["dvlab-research/MASA-SR"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":5,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/permutation-invariance-and-uncertainty-in","slug":"permutation-invariance-and-uncertainty-in","title":"Permutation invariance and uncertainty in multitemporal image super-resolution","date":"2021-05-26","arxiv_id":"2105.12409","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/permutation-invariance-and-uncertainty-in#ran","syntology_url":"https://syntology.ai/paper/2105.12409","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.12409"}},"official":{"repos":["diegovalsesia/piunet"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lapar-linearly-assembled-pixel-adaptive-1","slug":"lapar-linearly-assembled-pixel-adaptive-1","title":"LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond","date":"2021-05-21","arxiv_id":"2105.10422","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lapar-linearly-assembled-pixel-adaptive-1#ran","syntology_url":"https://syntology.ai/paper/2105.10422","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.10422"}},"official":{"repos":["dvlab-research/Simple-SR"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/srwarp-generalized-image-super-resolution","slug":"srwarp-generalized-image-super-resolution","title":"SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation","date":"2021-04-21","arxiv_id":"2104.10325","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/srwarp-generalized-image-super-resolution#ran","syntology_url":"https://syntology.ai/paper/2104.10325","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.10325"}},"official":{"repos":["sanghyun-son/srwarp"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/attention-in-attention-network-for-image","slug":"attention-in-attention-network-for-image","title":"Attention in Attention Network for Image Super-Resolution","date":"2021-04-19","arxiv_id":"2104.09497","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/attention-in-attention-network-for-image#ran","syntology_url":"https://syntology.ai/paper/2104.09497","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.09497"}},"official":{"repos":["haoyuc/A2N"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/image-super-resolution-via-iterative","slug":"image-super-resolution-via-iterative","title":"Image Super-Resolution via Iterative Refinement","date":"2021-04-15","arxiv_id":"2104.07636","repositories_listed":4,"syntology":{"n":3,"n_ran":2,"n_constructed":1,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/image-super-resolution-via-iterative#ran","syntology_url":"https://syntology.ai/paper/2104.07636","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.07636"}},"official":null}},{"url":"/paper/flow-based-kernel-prior-with-application-to","slug":"flow-based-kernel-prior-with-application-to","title":"Flow-based Kernel Prior with Application to Blind Super-Resolution","date":"2021-03-29","arxiv_id":"2103.15977","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/flow-based-kernel-prior-with-application-to#ran","syntology_url":"https://syntology.ai/paper/2103.15977","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.15977"}},"official":{"repos":["JingyunLiang/FKP"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/designing-a-practical-degradation-model-for","slug":"designing-a-practical-degradation-model-for","title":"Designing a Practical Degradation Model for Deep Blind Image Super-Resolution","date":"2021-03-25","arxiv_id":"2103.14006","repositories_listed":3,"syntology":{"n":12,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":7,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/designing-a-practical-degradation-model-for#ran","syntology_url":"https://syntology.ai/paper/2103.14006","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.14006"}},"official":{"repos":["cszn/BSRGAN"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/protecting-intellectual-property-of","slug":"protecting-intellectual-property-of","title":"Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack","date":"2021-02-08","arxiv_id":"2102.04362","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/protecting-intellectual-property-of#ran","syntology_url":"https://syntology.ai/paper/2102.04362","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.04362"}},"official":{"repos":["dingsheng-ong/ipr-gan"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/deep-burst-super-resolution","slug":"deep-burst-super-resolution","title":"Deep Burst Super-Resolution","date":"2021-01-26","arxiv_id":"2101.10997","repositories_listed":3,"syntology":{"n":7,"n_ran":6,"n_constructed":2,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":7,"phrase":"6 ran (of which 2 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/deep-burst-super-resolution#ran","syntology_url":"https://syntology.ai/paper/2101.10997","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2101.10997"}},"official":null}},{"url":"/paper/residual-feature-distillation-network-for","slug":"residual-feature-distillation-network-for","title":"Residual Feature Distillation Network for Lightweight Image Super-Resolution","date":"2020-09-24","arxiv_id":"2009.11551","repositories_listed":2,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":4,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/residual-feature-distillation-network-for#ran","syntology_url":"https://syntology.ai/paper/2009.11551","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.11551"}},"official":{"repos":["njulj/RFDN"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/deep-cyclic-generative-adversarial-residual","slug":"deep-cyclic-generative-adversarial-residual","title":"Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution","date":"2020-09-07","arxiv_id":"2009.03693","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-cyclic-generative-adversarial-residual#ran","syntology_url":"https://syntology.ai/paper/2009.03693","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.03693"}},"official":{"repos":["RaoUmer/SRResCycGAN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/deep-iterative-residual-convolutional-network","slug":"deep-iterative-residual-convolutional-network","title":"Deep Iterative Residual Convolutional Network for Single Image Super-Resolution","date":"2020-09-07","arxiv_id":"2009.04809","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-iterative-residual-convolutional-network#ran","syntology_url":"https://syntology.ai/paper/2009.04809","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.04809"}},"official":{"repos":["RaoUmer/ISRResCNet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/srflow-learning-the-super-resolution-space","slug":"srflow-learning-the-super-resolution-space","title":"SRFlow: Learning the Super-Resolution Space with Normalizing Flow","date":"2020-06-25","arxiv_id":"2006.14200","repositories_listed":8,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/srflow-learning-the-super-resolution-space#ran","syntology_url":"https://syntology.ai/paper/2006.14200","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.14200"}},"official":{"repos":["andreas128/SRFlow"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/learning-texture-transformer-network-for-1","slug":"learning-texture-transformer-network-for-1","title":"Learning Texture Transformer Network for Image Super-Resolution","date":"2020-06-07","arxiv_id":"2006.04139","repositories_listed":2,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":3,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-texture-transformer-network-for-1#ran","syntology_url":"https://syntology.ai/paper/2006.04139","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.04139"}},"official":{"repos":["researchmm/TTSR"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/perceptual-extreme-super-resolution-network","slug":"perceptual-extreme-super-resolution-network","title":"Perceptual Extreme Super Resolution Network with Receptive Field Block","date":"2020-05-26","arxiv_id":"2005.12597","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/perceptual-extreme-super-resolution-network#ran","syntology_url":"https://syntology.ai/paper/2005.12597","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.12597"}},"official":null}},{"url":"/paper/invertible-image-rescaling","slug":"invertible-image-rescaling","title":"Invertible Image Rescaling","date":"2020-05-12","arxiv_id":"2005.05650","repositories_listed":11,"syntology":{"n":17,"n_ran":15,"n_constructed":0,"n_ran_checked":14,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":3,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/invertible-image-rescaling#ran","syntology_url":"https://syntology.ai/paper/2005.05650","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.05650"}},"official":{"repos":["pkuxmq/Invertible-Image-Rescaling"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/ntire-2020-challenge-on-real-world-image","slug":"ntire-2020-challenge-on-real-world-image","title":"NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results","date":"2020-05-05","arxiv_id":"2005.01996","repositories_listed":5,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ntire-2020-challenge-on-real-world-image#ran","syntology_url":"https://syntology.ai/paper/2005.01996","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.01996"}},"official":null}},{"url":"/paper/deep-generative-adversarial-residual","slug":"deep-generative-adversarial-residual","title":"Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution","date":"2020-05-03","arxiv_id":"2005.00953","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-generative-adversarial-residual#ran","syntology_url":"https://syntology.ai/paper/2005.00953","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00953"}},"official":{"repos":["RaoUmer/SRResCGAN"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-for-scale-arbitrary-super-resolution","slug":"learning-for-scale-arbitrary-super-resolution","title":"Learning A Single Network for Scale-Arbitrary Super-Resolution","date":"2020-04-08","arxiv_id":"2004.03791","repositories_listed":2,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-for-scale-arbitrary-super-resolution#ran","syntology_url":"https://syntology.ai/paper/2004.03791","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.03791"}},"official":null}},{"url":"/paper/rethinking-data-augmentation-for-image-super","slug":"rethinking-data-augmentation-for-image-super","title":"Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy","date":"2020-04-01","arxiv_id":"2004.00448","repositories_listed":2,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rethinking-data-augmentation-for-image-super#ran","syntology_url":"https://syntology.ai/paper/2004.00448","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.00448"}},"official":{"repos":["clovaai/cutblur"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/dhp-differentiable-meta-pruning-via","slug":"dhp-differentiable-meta-pruning-via","title":"DHP: Differentiable Meta Pruning via HyperNetworks","date":"2020-03-30","arxiv_id":"2003.13683","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/dhp-differentiable-meta-pruning-via#ran","syntology_url":"https://syntology.ai/paper/2003.13683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.13683"}},"official":{"repos":["ofsoundof/dhp"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/deep-unfolding-network-for-image-super","slug":"deep-unfolding-network-for-image-super","title":"Deep Unfolding Network for Image Super-Resolution","date":"2020-03-23","arxiv_id":"2003.10428","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-unfolding-network-for-image-super#ran","syntology_url":"https://syntology.ai/paper/2003.10428","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10428"}},"official":{"repos":["cszn/USRNet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/closed-loop-matters-dual-regression-networks","slug":"closed-loop-matters-dual-regression-networks","title":"Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution","date":"2020-03-16","arxiv_id":"2003.07018","repositories_listed":3,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/closed-loop-matters-dual-regression-networks#ran","syntology_url":"https://syntology.ai/paper/2003.07018","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.07018"}},"official":{"repos":["guoyongcs/DRN"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/pulse-self-supervised-photo-upsampling-via","slug":"pulse-self-supervised-photo-upsampling-via","title":"PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models","date":"2020-03-08","arxiv_id":"2003.03808","repositories_listed":16,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/pulse-self-supervised-photo-upsampling-via#ran","syntology_url":"https://syntology.ai/paper/2003.03808","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.03808"}},"official":{"repos":["adamian98/pulse"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/creating-high-resolution-images-with-a-latent","slug":"creating-high-resolution-images-with-a-latent","title":"Creating High Resolution Images with a Latent Adversarial Generator","date":"2020-03-04","arxiv_id":"2003.02365","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/creating-high-resolution-images-with-a-latent#ran","syntology_url":"https://syntology.ai/paper/2003.02365","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.02365"}},"official":{"repos":["google-research/lag"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/meta-transfer-learning-for-zero-shot-super","slug":"meta-transfer-learning-for-zero-shot-super","title":"Meta-Transfer Learning for Zero-Shot Super-Resolution","date":"2020-02-27","arxiv_id":"2002.12213","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/meta-transfer-learning-for-zero-shot-super#ran","syntology_url":"https://syntology.ai/paper/2002.12213","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.12213"}},"official":{"repos":["JWSoh/MZSR"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/explorable-super-resolution","slug":"explorable-super-resolution","title":"Explorable Super Resolution","date":"2019-12-04","arxiv_id":"1912.01839","repositories_listed":2,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/explorable-super-resolution#ran","syntology_url":"https://syntology.ai/paper/1912.01839","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.01839"}},"official":{"repos":["YuvalBahat/Explorable-Super-Resolution"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/frequency-separation-for-real-world-super","slug":"frequency-separation-for-real-world-super","title":"Frequency Separation for Real-World Super-Resolution","date":"2019-11-18","arxiv_id":"1911.07850","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 1 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/frequency-separation-for-real-world-super#ran","syntology_url":"https://syntology.ai/paper/1911.07850","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.07850"}},"official":{"repos":["ManuelFritsche/real-world-sr"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/lightweight-image-super-resolution-with-1","slug":"lightweight-image-super-resolution-with-1","title":"Lightweight Image Super-Resolution with Information Multi-distillation Network","date":"2019-09-26","arxiv_id":"1909.11856","repositories_listed":4,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/lightweight-image-super-resolution-with-1#ran","syntology_url":"https://syntology.ai/paper/1909.11856","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.11856"}},"official":{"repos":["Zheng222/IMDN"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/learning-filter-basis-for-convolutional","slug":"learning-filter-basis-for-convolutional","title":"Learning Filter Basis for Convolutional Neural Network Compression","date":"2019-08-23","arxiv_id":"1908.08932","repositories_listed":3,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":3,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-filter-basis-for-convolutional#ran","syntology_url":"https://syntology.ai/paper/1908.08932","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08932"}},"official":{"repos":["ofsoundof/learning_filter_basis"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/densely-residual-laplacian-super-resolution","slug":"densely-residual-laplacian-super-resolution","title":"Densely Residual Laplacian Super-Resolution","date":"2019-06-28","arxiv_id":"1906.12021","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/densely-residual-laplacian-super-resolution#ran","syntology_url":"https://syntology.ai/paper/1906.12021","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.12021"}},"official":null}},{"url":"/paper/generative-adversarial-networks-a-survey-and","slug":"generative-adversarial-networks-a-survey-and","title":"Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy","date":"2019-06-04","arxiv_id":"1906.01529","repositories_listed":2,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/generative-adversarial-networks-a-survey-and#ran","syntology_url":"https://syntology.ai/paper/1906.01529","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.01529"}},"official":{"repos":["sheqi/GAN_Review"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/singan-learning-a-generative-model-from-a","slug":"singan-learning-a-generative-model-from-a","title":"SinGAN: Learning a Generative Model from a Single Natural Image","date":"2019-05-02","arxiv_id":"1905.01164","repositories_listed":47,"syntology":{"n":11,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/singan-learning-a-generative-model-from-a#ran","syntology_url":"https://syntology.ai/paper/1905.01164","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.01164"}},"official":{"repos":["tamarott/SinGAN"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/blind-super-resolution-with-iterative-kernel","slug":"blind-super-resolution-with-iterative-kernel","title":"Blind Super-Resolution With Iterative Kernel Correction","date":"2019-04-06","arxiv_id":"1904.03377","repositories_listed":3,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/blind-super-resolution-with-iterative-kernel#ran","syntology_url":"https://syntology.ai/paper/1904.03377","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.03377"}},"official":null}},{"url":"/paper/recurrent-back-projection-network-for-video","slug":"recurrent-back-projection-network-for-video","title":"Recurrent Back-Projection Network for Video Super-Resolution","date":"2019-03-25","arxiv_id":"1903.10128","repositories_listed":7,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/recurrent-back-projection-network-for-video#ran","syntology_url":"https://syntology.ai/paper/1903.10128","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.10128"}},"official":null}},{"url":"/paper/feedback-network-for-image-super-resolution","slug":"feedback-network-for-image-super-resolution","title":"Feedback Network for Image Super-Resolution","date":"2019-03-23","arxiv_id":"1903.09814","repositories_listed":4,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/feedback-network-for-image-super-resolution#ran","syntology_url":"https://syntology.ai/paper/1903.09814","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.09814"}},"official":{"repos":["Paper99/SRFBN_CVPR19"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-parallax-attention-for-stereo-image","slug":"learning-parallax-attention-for-stereo-image","title":"Learning Parallax Attention for Stereo Image Super-Resolution","date":"2019-03-14","arxiv_id":"1903.05784","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-parallax-attention-for-stereo-image#ran","syntology_url":"https://syntology.ai/paper/1903.05784","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.05784"}},"official":{"repos":["LongguangWang/PASSRnet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/universally-slimmable-networks-and-improved","slug":"universally-slimmable-networks-and-improved","title":"Universally Slimmable Networks and Improved Training Techniques","date":"2019-03-12","arxiv_id":"1903.05134","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/universally-slimmable-networks-and-improved#ran","syntology_url":"https://syntology.ai/paper/1903.05134","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.05134"}},"official":{"repos":["JiahuiYu/slimmable_networks"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/image-super-resolution-by-neural-texture","slug":"image-super-resolution-by-neural-texture","title":"Image Super-Resolution by Neural Texture Transfer","date":"2019-03-03","arxiv_id":"1903.00834","repositories_listed":2,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/image-super-resolution-by-neural-texture#ran","syntology_url":"https://syntology.ai/paper/1903.00834","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.00834"}},"official":{"repos":["ZZUTK/SRNTT"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/meta-sr-a-magnification-arbitrary-network-for","slug":"meta-sr-a-magnification-arbitrary-network-for","title":"Meta-SR: A Magnification-Arbitrary Network for Super-Resolution","date":"2019-03-03","arxiv_id":"1903.00875","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/meta-sr-a-magnification-arbitrary-network-for#ran","syntology_url":"https://syntology.ai/paper/1903.00875","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1903.00875"}},"official":null}},{"url":"/paper/progressive-image-deraining-networks-a-better","slug":"progressive-image-deraining-networks-a-better","title":"Progressive Image Deraining Networks: A Better and Simpler Baseline","date":"2019-01-26","arxiv_id":"1901.09221","repositories_listed":4,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/progressive-image-deraining-networks-a-better#ran","syntology_url":"https://syntology.ai/paper/1901.09221","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1901.09221"}},"official":{"repos":["csdwren/PReNet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/a-comprehensive-guide-to-bayesian","slug":"a-comprehensive-guide-to-bayesian","title":"A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference","date":"2019-01-08","arxiv_id":"1901.02731","repositories_listed":6,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":10,"n_instrument":4,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":2,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/a-comprehensive-guide-to-bayesian#ran","syntology_url":"https://syntology.ai/paper/1901.02731","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1901.02731"}},"official":{"repos":["kumar-shridhar/PyTorch-BayesianCNN"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/temporally-coherent-gans-for-video-super","slug":"temporally-coherent-gans-for-video-super","title":"Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation","date":"2018-11-23","arxiv_id":"1811.09393","repositories_listed":13,"syntology":{"n":25,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":14,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 14 unverified","sample_list":"/paper/temporally-coherent-gans-for-video-super#ran","syntology_url":"https://syntology.ai/paper/1811.09393","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.09393"}},"official":{"repos":["thunil/TecoGAN"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":10,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/deep-learning-based-channel-estimation","slug":"deep-learning-based-channel-estimation","title":"Deep Learning-Based Channel Estimation","date":"2018-10-13","arxiv_id":"1810.05893","repositories_listed":4,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-learning-based-channel-estimation#ran","syntology_url":"https://syntology.ai/paper/1810.05893","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.05893"}},"official":{"repos":["Mehran-Soltani/ChannelNet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/esrgan-enhanced-super-resolution-generative","slug":"esrgan-enhanced-super-resolution-generative","title":"ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks","date":"2018-09-01","arxiv_id":"1809.00219","repositories_listed":46,"syntology":{"n":44,"n_ran":33,"n_constructed":0,"n_ran_checked":29,"n_instrument":4,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":29,"n_pointer_only":7,"phrase":"33 ran (of which 0 constructed an object rather than computing a result; 29 with no instrument failure: 0 honoured, 0 violated, 29 with no contract checked; 4 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/esrgan-enhanced-super-resolution-generative#ran","syntology_url":"https://syntology.ai/paper/1809.00219","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1809.00219"}},"official":{"repos":["xinntao/ESRGAN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/wide-activation-for-efficient-and-accurate","slug":"wide-activation-for-efficient-and-accurate","title":"Wide Activation for Efficient and Accurate Image Super-Resolution","date":"2018-08-27","arxiv_id":"1808.08718","repositories_listed":12,"syntology":{"n":17,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/wide-activation-for-efficient-and-accurate#ran","syntology_url":"https://syntology.ai/paper/1808.08718","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1808.08718"}},"official":{"repos":["JiahuiYu/wdsr_ntire2018"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/to-learn-image-super-resolution-use-a-gan-to","slug":"to-learn-image-super-resolution-use-a-gan-to","title":"To learn image super-resolution, use a GAN to learn how to do image degradation first","date":"2018-07-30","arxiv_id":"1807.11458","repositories_listed":2,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":0,"n_instrument":4,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/to-learn-image-super-resolution-use-a-gan-to#ran","syntology_url":"https://syntology.ai/paper/1807.11458","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.11458"}},"official":null}},{"url":"/paper/image-super-resolution-using-very-deep","slug":"image-super-resolution-using-very-deep","title":"Image Super-Resolution Using Very Deep Residual Channel Attention Networks","date":"2018-07-08","arxiv_id":"1807.02758","repositories_listed":20,"syntology":{"n":22,"n_ran":17,"n_constructed":6,"n_ran_checked":16,"n_instrument":1,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":16,"n_pointer_only":3,"phrase":"17 ran (of which 6 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/image-super-resolution-using-very-deep#ran","syntology_url":"https://syntology.ai/paper/1807.02758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.02758"}},"official":{"repos":["yulunzhang/RCAN"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/fast-accurate-and-lightweight-super-1","slug":"fast-accurate-and-lightweight-super-1","title":"Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network","date":"2018-03-23","arxiv_id":"1803.08664","repositories_listed":3,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/fast-accurate-and-lightweight-super-1#ran","syntology_url":"https://syntology.ai/paper/1803.08664","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.08664"}},"official":null}},{"url":"/paper/maintaining-natural-image-statistics-with-the","slug":"maintaining-natural-image-statistics-with-the","title":"Maintaining Natural Image Statistics with the Contextual Loss","date":"2018-03-13","arxiv_id":"1803.04626","repositories_listed":3,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/maintaining-natural-image-statistics-with-the#ran","syntology_url":"https://syntology.ai/paper/1803.04626","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.04626"}},"official":null}},{"url":"/paper/deep-back-projection-networks-for-super","slug":"deep-back-projection-networks-for-super","title":"Deep Back-Projection Networks For Super-Resolution","date":"2018-03-07","arxiv_id":"1803.02735","repositories_listed":16,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":13,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":12,"n_pointer_only":4,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 1 violated, 12 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-back-projection-networks-for-super#ran","syntology_url":"https://syntology.ai/paper/1803.02735","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.02735"}},"official":null}},{"url":"/paper/residual-dense-network-for-image-super","slug":"residual-dense-network-for-image-super","title":"Residual Dense Network for Image Super-Resolution","date":"2018-02-24","arxiv_id":"1802.08797","repositories_listed":16,"syntology":{"n":24,"n_ran":20,"n_constructed":0,"n_ran_checked":15,"n_instrument":5,"n_unverified":4,"n_honours":2,"n_violates":0,"n_no_contract":13,"n_pointer_only":4,"phrase":"20 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 2 honoured, 0 violated, 13 with no contract checked; 5 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/residual-dense-network-for-image-super#ran","syntology_url":"https://syntology.ai/paper/1802.08797","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1802.08797"}},"official":{"repos":["yulunzhang/RDN"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/fast-and-accurate-image-super-resolution-with","slug":"fast-and-accurate-image-super-resolution-with","title":"Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks","date":"2017-10-04","arxiv_id":"1710.01992","repositories_listed":7,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/fast-and-accurate-image-super-resolution-with#ran","syntology_url":"https://syntology.ai/paper/1710.01992","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1710.01992"}},"official":null}},{"url":"/paper/enhanced-deep-residual-networks-for-single","slug":"enhanced-deep-residual-networks-for-single","title":"Enhanced Deep Residual Networks for Single Image Super-Resolution","date":"2017-07-10","arxiv_id":"1707.02921","repositories_listed":45,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/enhanced-deep-residual-networks-for-single#ran","syntology_url":"https://syntology.ai/paper/1707.02921","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1707.02921"}},"official":{"repos":["LimBee/NTIRE2017"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/real-time-single-image-and-video-super","slug":"real-time-single-image-and-video-super","title":"Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network","date":"2016-09-16","arxiv_id":"1609.05158","repositories_listed":47,"syntology":{"n":20,"n_ran":19,"n_constructed":0,"n_ran_checked":15,"n_instrument":4,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":1,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/real-time-single-image-and-video-super#ran","syntology_url":"https://syntology.ai/paper/1609.05158","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1609.05158"}},"official":null}},{"url":"/paper/photo-realistic-single-image-super-resolution","slug":"photo-realistic-single-image-super-resolution","title":"Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network","date":"2016-09-15","arxiv_id":"1609.04802","repositories_listed":140,"syntology":{"n":72,"n_ran":55,"n_constructed":0,"n_ran_checked":45,"n_instrument":10,"n_unverified":17,"n_honours":3,"n_violates":3,"n_no_contract":39,"n_pointer_only":14,"phrase":"55 ran (of which 0 constructed an object rather than computing a result; 45 with no instrument failure: 3 honoured, 3 violated, 39 with no contract checked; 10 where Syntology's instrument failed) · 17 unverified","sample_list":"/paper/photo-realistic-single-image-super-resolution#ran","syntology_url":"https://syntology.ai/paper/1609.04802","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1609.04802"}},"official":null}},{"url":"/paper/beyond-a-gaussian-denoiser-residual-learning","slug":"beyond-a-gaussian-denoiser-residual-learning","title":"Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising","date":"2016-08-13","arxiv_id":"1608.03981","repositories_listed":22,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/beyond-a-gaussian-denoiser-residual-learning#ran","syntology_url":"https://syntology.ai/paper/1608.03981","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1608.03981"}},"official":{"repos":["cszn/DnCNN"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/accelerating-the-super-resolution","slug":"accelerating-the-super-resolution","title":"Accelerating the Super-Resolution Convolutional Neural Network","date":"2016-08-01","arxiv_id":"1608.00367","repositories_listed":16,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":14,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 0 violated, 14 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/accelerating-the-super-resolution#ran","syntology_url":"https://syntology.ai/paper/1608.00367","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1608.00367"}},"official":null}},{"url":"/paper/perceptual-losses-for-real-time-style","slug":"perceptual-losses-for-real-time-style","title":"Perceptual Losses for Real-Time Style Transfer and Super-Resolution","date":"2016-03-27","arxiv_id":"1603.08155","repositories_listed":80,"syntology":{"n":46,"n_ran":34,"n_constructed":0,"n_ran_checked":29,"n_instrument":5,"n_unverified":12,"n_honours":1,"n_violates":2,"n_no_contract":26,"n_pointer_only":9,"phrase":"34 ran (of which 0 constructed an object rather than computing a result; 29 with no instrument failure: 1 honoured, 2 violated, 26 with no contract checked; 5 where Syntology's instrument failed) · 12 unverified","sample_list":"/paper/perceptual-losses-for-real-time-style#ran","syntology_url":"https://syntology.ai/paper/1603.08155","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1603.08155"}},"official":null}},{"url":"/paper/deeply-recursive-convolutional-network-for","slug":"deeply-recursive-convolutional-network-for","title":"Deeply-Recursive Convolutional Network for Image Super-Resolution","date":"2015-11-14","arxiv_id":"1511.04491","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deeply-recursive-convolutional-network-for#ran","syntology_url":"https://syntology.ai/paper/1511.04491","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1511.04491"}},"official":null}},{"url":"/paper/accurate-image-super-resolution-using-very","slug":"accurate-image-super-resolution-using-very","title":"Accurate Image Super-Resolution Using Very Deep Convolutional Networks","date":"2015-11-14","arxiv_id":"1511.04587","repositories_listed":8,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/accurate-image-super-resolution-using-very#ran","syntology_url":"https://syntology.ai/paper/1511.04587","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1511.04587"}},"official":null}},{"url":"/paper/image-super-resolution-using-deep","slug":"image-super-resolution-using-deep","title":"Image Super-Resolution Using Deep Convolutional Networks","date":"2014-12-31","arxiv_id":"1501.00092","repositories_listed":60,"syntology":{"n":27,"n_ran":21,"n_constructed":0,"n_ran_checked":17,"n_instrument":4,"n_unverified":6,"n_honours":3,"n_violates":0,"n_no_contract":14,"n_pointer_only":7,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 17 with no instrument failure: 3 honoured, 0 violated, 14 with no contract checked; 4 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/image-super-resolution-using-deep#ran","syntology_url":"https://syntology.ai/paper/1501.00092","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1501.00092"}},"official":null}}],"record_sha256":"230bc72670cfffaaf7e9b55d7e7eb5ebfb5ea37d95dbace9a4b56906e9955c4c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}