{"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/nerf/papers/ran/3","list_of":"/task/nerf","task":"NeRF","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":3,"pages_in_order":3,"rows_per_page":100,"rows":[201,248],"of":248,"counts":{"archive_papers_tagged":1713,"with_a_code_link":631,"where_syntology_ran_a_sample":248,"not_listed_spam_title":0,"listed":1713,"listed_where_code_ran":248,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":207,"every_run_a_failure_of_syntologys_instrument":41,"listed_with_a_run_with_no_instrument_failure":207,"listed_every_run_a_failure_of_syntologys_instrument":41,"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/nerf/papers/ran/1","prev":"/task/nerf/papers/ran/2","next":null,"papers":[{"url":"/paper/conditional-flow-nerf-accurate-3d-modelling","slug":"conditional-flow-nerf-accurate-3d-modelling","title":"Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification","date":"2022-03-18","arxiv_id":"2203.10192","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"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) · 2 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/conditional-flow-nerf-accurate-3d-modelling#ran","syntology_url":"https://syntology.ai/paper/2203.10192","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10192"}},"official":{"repos":["poetrywanderer/CF-NeRF"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/kubric-a-scalable-dataset-generator","slug":"kubric-a-scalable-dataset-generator","title":"Kubric: A scalable dataset generator","date":"2022-03-07","arxiv_id":"2203.03570","repositories_listed":1,"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/kubric-a-scalable-dataset-generator#ran","syntology_url":"https://syntology.ai/paper/2203.03570","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.03570"}},"official":{"repos":["google-research/kubric"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/block-nerf-scalable-large-scene-neural-view","slug":"block-nerf-scalable-large-scene-neural-view","title":"Block-NeRF: Scalable Large Scene Neural View Synthesis","date":"2022-02-10","arxiv_id":"2202.05263","repositories_listed":1,"syntology":{"n":14,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":5,"phrase":"10 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; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/block-nerf-scalable-large-scene-neural-view#ran","syntology_url":"https://syntology.ai/paper/2202.05263","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.05263"}},"official":null}},{"url":"/paper/from-data-to-functa-your-data-point-is-a","slug":"from-data-to-functa-your-data-point-is-a","title":"From data to functa: Your data point is a function and you can treat it like one","date":"2022-01-28","arxiv_id":"2201.12204","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"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) · 2 unverified","sample_list":"/paper/from-data-to-functa-your-data-point-is-a#ran","syntology_url":"https://syntology.ai/paper/2201.12204","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.12204"}},"official":{"repos":["deepmind/functa"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mega-nerf-scalable-construction-of-large","slug":"mega-nerf-scalable-construction-of-large","title":"Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs","date":"2021-12-20","arxiv_id":"2112.10703","repositories_listed":2,"syntology":{"n":7,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"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) · 3 unverified","sample_list":"/paper/mega-nerf-scalable-construction-of-large#ran","syntology_url":"https://syntology.ai/paper/2112.10703","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.10703"}},"official":{"repos":["cmusatyalab/mega-nerf"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/3d-aware-image-synthesis-via-learning","slug":"3d-aware-image-synthesis-via-learning","title":"3D-aware Image Synthesis via Learning Structural and Textural Representations","date":"2021-12-20","arxiv_id":"2112.10759","repositories_listed":1,"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":3,"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/3d-aware-image-synthesis-via-learning#ran","syntology_url":"https://syntology.ai/paper/2112.10759","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.10759"}},"official":{"repos":["genforce/volumegan"],"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/headnerf-a-real-time-nerf-based-parametric","slug":"headnerf-a-real-time-nerf-based-parametric","title":"HeadNeRF: A Real-time NeRF-based Parametric Head Model","date":"2021-12-10","arxiv_id":"2112.05637","repositories_listed":1,"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/headnerf-a-real-time-nerf-based-parametric#ran","syntology_url":"https://syntology.ai/paper/2112.05637","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.05637"}},"official":{"repos":["crishy1995/headnerf"],"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/clip-nerf-text-and-image-driven-manipulation","slug":"clip-nerf-text-and-image-driven-manipulation","title":"CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields","date":"2021-12-09","arxiv_id":"2112.05139","repositories_listed":2,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/clip-nerf-text-and-image-driven-manipulation#ran","syntology_url":"https://syntology.ai/paper/2112.05139","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.05139"}},"official":{"repos":["cassiePython/CLIPNeRF"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/dense-depth-priors-for-neural-radiance-fields","slug":"dense-depth-priors-for-neural-radiance-fields","title":"Dense Depth Priors for Neural Radiance Fields from Sparse Input Views","date":"2021-12-06","arxiv_id":"2112.03288","repositories_listed":1,"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":1,"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/dense-depth-priors-for-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2112.03288","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.03288"}},"official":{"repos":["barbararoessle/dense_depth_priors_nerf"],"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","unlocated"]}}},{"url":"/paper/mofanerf-morphable-facial-neural-radiance","slug":"mofanerf-morphable-facial-neural-radiance","title":"MoFaNeRF: Morphable Facial Neural Radiance Field","date":"2021-12-04","arxiv_id":"2112.02308","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/mofanerf-morphable-facial-neural-radiance#ran","syntology_url":"https://syntology.ai/paper/2112.02308","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.02308"}},"official":{"repos":["zhuhao-nju/mofanerf"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-sr-high-quality-neural-radiance-fields","slug":"nerf-sr-high-quality-neural-radiance-fields","title":"NeRF-SR: High-Quality Neural Radiance Fields using Supersampling","date":"2021-12-03","arxiv_id":"2112.01759","repositories_listed":2,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/nerf-sr-high-quality-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2112.01759","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.01759"}},"official":{"repos":["cwchenwang/NeRF-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/learning-neural-light-fields-with-ray-space","slug":"learning-neural-light-fields-with-ray-space","title":"Learning Neural Light Fields with Ray-Space Embedding Networks","date":"2021-12-02","arxiv_id":"2112.01523","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"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) · 1 unverified","sample_list":"/paper/learning-neural-light-fields-with-ray-space#ran","syntology_url":"https://syntology.ai/paper/2112.01523","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.01523"}},"official":{"repos":["facebookresearch/neural-light-fields"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/hallucinated-neural-radiance-fields-in-the","slug":"hallucinated-neural-radiance-fields-in-the","title":"Hallucinated Neural Radiance Fields in the Wild","date":"2021-11-30","arxiv_id":"2111.15246","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":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) · 0 unverified","sample_list":"/paper/hallucinated-neural-radiance-fields-in-the#ran","syntology_url":"https://syntology.ai/paper/2111.15246","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.15246"}},"official":null}},{"url":"/paper/deblur-nerf-neural-radiance-fields-from","slug":"deblur-nerf-neural-radiance-fields-from","title":"Deblur-NeRF: Neural Radiance Fields from Blurry Images","date":"2021-11-29","arxiv_id":"2111.14292","repositories_listed":1,"syntology":{"n":10,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":8,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 1 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deblur-nerf-neural-radiance-fields-from#ran","syntology_url":"https://syntology.ai/paper/2111.14292","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.14292"}},"official":{"repos":["limacv/Deblur-NeRF"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-in-the-dark-high-dynamic-range-view","slug":"nerf-in-the-dark-high-dynamic-range-view","title":"NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images","date":"2021-11-26","arxiv_id":"2111.13679","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/nerf-in-the-dark-high-dynamic-range-view#ran","syntology_url":"https://syntology.ai/paper/2111.13679","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.13679"}},"official":{"repos":["google-research/multinerf"],"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/direct-voxel-grid-optimization-super-fast","slug":"direct-voxel-grid-optimization-super-fast","title":"Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction","date":"2021-11-22","arxiv_id":"2111.11215","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":3,"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/direct-voxel-grid-optimization-super-fast#ran","syntology_url":"https://syntology.ai/paper/2111.11215","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.11215"}},"official":{"repos":["sunset1995/directvoxgo"],"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/cips-3d-a-3d-aware-generator-of-gans-based-on","slug":"cips-3d-a-3d-aware-generator-of-gans-based-on","title":"CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis","date":"2021-10-19","arxiv_id":"2110.09788","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":4,"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) · 4 unverified","sample_list":"/paper/cips-3d-a-3d-aware-generator-of-gans-based-on#ran","syntology_url":"https://syntology.ai/paper/2110.09788","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.09788"}},"official":{"repos":["PeterouZh/CIPS-3D"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/stylenerf-a-style-based-3d-aware-generator-1","slug":"stylenerf-a-style-based-3d-aware-generator-1","title":"StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis","date":"2021-10-18","arxiv_id":"2110.08985","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":1,"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/stylenerf-a-style-based-3d-aware-generator-1#ran","syntology_url":"https://syntology.ai/paper/2110.08985","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08985"}},"official":{"repos":["facebookresearch/StyleNeRF"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/ners-neural-reflectance-surfaces-for-sparse","slug":"ners-neural-reflectance-surfaces-for-sparse","title":"NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild","date":"2021-10-14","arxiv_id":"2110.07604","repositories_listed":1,"syntology":{"n":14,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/ners-neural-reflectance-surfaces-for-sparse#ran","syntology_url":"https://syntology.ai/paper/2110.07604","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.07604"}},"official":{"repos":["jasonyzhang/ners"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/torf-time-of-flight-radiance-fields-for","slug":"torf-time-of-flight-radiance-fields-for","title":"TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis","date":"2021-09-30","arxiv_id":"2109.15271","repositories_listed":1,"syntology":{"n":20,"n_ran":14,"n_constructed":0,"n_ran_checked":9,"n_instrument":5,"n_unverified":6,"n_honours":4,"n_violates":2,"n_no_contract":3,"n_pointer_only":0,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 4 honoured, 2 violated, 3 with no contract checked; 5 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/torf-time-of-flight-radiance-fields-for#ran","syntology_url":"https://syntology.ai/paper/2109.15271","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.15271"}},"official":{"repos":["breuckelen/torf"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/codenerf-disentangled-neural-radiance-fields","slug":"codenerf-disentangled-neural-radiance-fields","title":"CodeNeRF: Disentangled Neural Radiance Fields for Object Categories","date":"2021-09-03","arxiv_id":"2109.01750","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/codenerf-disentangled-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2109.01750","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.01750"}},"official":{"repos":["wayne1123/code-nerf"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/nerfingmvs-guided-optimization-of-neural","slug":"nerfingmvs-guided-optimization-of-neural","title":"NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo","date":"2021-09-02","arxiv_id":"2109.01129","repositories_listed":1,"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":0,"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/nerfingmvs-guided-optimization-of-neural#ran","syntology_url":"https://syntology.ai/paper/2109.01129","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.01129"}},"official":{"repos":["weiyithu/nerfingmvs"],"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/depth-supervised-nerf-fewer-views-and-faster","slug":"depth-supervised-nerf-fewer-views-and-faster","title":"Depth-supervised NeRF: Fewer Views and Faster Training for Free","date":"2021-07-06","arxiv_id":"2107.02791","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"3 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/depth-supervised-nerf-fewer-views-and-faster#ran","syntology_url":"https://syntology.ai/paper/2107.02791","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.02791"}},"official":{"repos":["dunbar12138/DSNeRF"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/hypernerf-a-higher-dimensional-representation","slug":"hypernerf-a-higher-dimensional-representation","title":"HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields","date":"2021-06-24","arxiv_id":"2106.13228","repositories_listed":2,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":13,"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, 1 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/hypernerf-a-higher-dimensional-representation#ran","syntology_url":"https://syntology.ai/paper/2106.13228","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.13228"}},"official":null}},{"url":"/paper/neus-learning-neural-implicit-surfaces-by","slug":"neus-learning-neural-implicit-surfaces-by","title":"NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction","date":"2021-06-20","arxiv_id":"2106.10689","repositories_listed":7,"syntology":{"n":16,"n_ran":14,"n_constructed":0,"n_ran_checked":8,"n_instrument":6,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":6,"n_pointer_only":5,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 2 honoured, 0 violated, 6 with no contract checked; 6 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/neus-learning-neural-implicit-surfaces-by#ran","syntology_url":"https://syntology.ai/paper/2106.10689","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.10689"}},"official":{"repos":["Totoro97/NeuS"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/nerfactor-neural-factorization-of-shape-and","slug":"nerfactor-neural-factorization-of-shape-and","title":"NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination","date":"2021-06-03","arxiv_id":"2106.01970","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/nerfactor-neural-factorization-of-shape-and#ran","syntology_url":"https://syntology.ai/paper/2106.01970","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.01970"}},"official":{"repos":["google/nerfactor"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/editing-conditional-radiance-fields","slug":"editing-conditional-radiance-fields","title":"Editing Conditional Radiance Fields","date":"2021-05-13","arxiv_id":"2105.06466","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/editing-conditional-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2105.06466","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.06466"}},"official":{"repos":["stevliu/editnerf"],"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/dynamic-view-synthesis-from-dynamic-monocular","slug":"dynamic-view-synthesis-from-dynamic-monocular","title":"Dynamic View Synthesis from Dynamic Monocular Video","date":"2021-05-13","arxiv_id":"2105.06468","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":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) · 0 unverified","sample_list":"/paper/dynamic-view-synthesis-from-dynamic-monocular#ran","syntology_url":"https://syntology.ai/paper/2105.06468","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.06468"}},"official":{"repos":["gaochen315/DynamicNeRF"],"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/shadow-neural-radiance-fields-for-multi-view","slug":"shadow-neural-radiance-fields-for-multi-view","title":"Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry","date":"2021-04-20","arxiv_id":"2104.09877","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":1,"n_no_contract":0,"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, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/shadow-neural-radiance-fields-for-multi-view#ran","syntology_url":"https://syntology.ai/paper/2104.09877","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.09877"}},"official":{"repos":["esa/snerf"],"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/unisurf-unifying-neural-implicit-surfaces-and","slug":"unisurf-unifying-neural-implicit-surfaces-and","title":"UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction","date":"2021-04-20","arxiv_id":"2104.10078","repositories_listed":2,"syntology":{"n":10,"n_ran":8,"n_constructed":6,"n_ran_checked":7,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"8 ran (of which 6 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/unisurf-unifying-neural-implicit-surfaces-and#ran","syntology_url":"https://syntology.ai/paper/2104.10078","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.10078"}},"official":{"repos":["autonomousvision/unisurf"],"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":["listed","official"]}}},{"url":"/paper/stereo-radiance-fields-srf-learning-view","slug":"stereo-radiance-fields-srf-learning-view","title":"Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes","date":"2021-04-14","arxiv_id":"2104.06935","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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) · 2 unverified","sample_list":"/paper/stereo-radiance-fields-srf-learning-view#ran","syntology_url":"https://syntology.ai/paper/2104.06935","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.06935"}},"official":null}},{"url":"/paper/barf-bundle-adjusting-neural-radiance-fields","slug":"barf-bundle-adjusting-neural-radiance-fields","title":"BARF: Bundle-Adjusting Neural Radiance Fields","date":"2021-04-13","arxiv_id":"2104.06405","repositories_listed":4,"syntology":{"n":19,"n_ran":12,"n_constructed":1,"n_ran_checked":11,"n_instrument":1,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"phrase":"12 ran (of which 1 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 1 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/barf-bundle-adjusting-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2104.06405","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.06405"}},"official":{"repos":["chenhsuanlin/bundle-adjusting-NeRF"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/neural-rgb-d-surface-reconstruction","slug":"neural-rgb-d-surface-reconstruction","title":"Neural RGB-D Surface Reconstruction","date":"2021-04-09","arxiv_id":"2104.04532","repositories_listed":2,"syntology":{"n":6,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":4,"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) · 4 unverified","sample_list":"/paper/neural-rgb-d-surface-reconstruction#ran","syntology_url":"https://syntology.ai/paper/2104.04532","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.04532"}},"official":{"repos":["dazinovic/neural-rgbd-surface-reconstruction"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/decomposing-3d-scenes-into-objects-via","slug":"decomposing-3d-scenes-into-objects-via","title":"Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation","date":"2021-04-02","arxiv_id":"2104.01148","repositories_listed":1,"syntology":{"n":13,"n_ran":13,"n_constructed":0,"n_ran_checked":13,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":13,"n_pointer_only":0,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/decomposing-3d-scenes-into-objects-via#ran","syntology_url":"https://syntology.ai/paper/2104.01148","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.01148"}},"official":{"repos":["stelzner/obsurf"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/putting-nerf-on-a-diet-semantically","slug":"putting-nerf-on-a-diet-semantically","title":"Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis","date":"2021-04-01","arxiv_id":"2104.00677","repositories_listed":2,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/putting-nerf-on-a-diet-semantically#ran","syntology_url":"https://syntology.ai/paper/2104.00677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.00677"}},"official":{"repos":["ajayjain/DietNeRF"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/foveated-neural-radiance-fields-for-real-time","slug":"foveated-neural-radiance-fields-for-real-time","title":"FoV-NeRF: Foveated Neural Radiance Fields for Virtual Reality","date":"2021-03-30","arxiv_id":"2103.16365","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/foveated-neural-radiance-fields-for-real-time#ran","syntology_url":"https://syntology.ai/paper/2103.16365","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.16365"}},"official":{"repos":["dengnianchen/fovnerf"],"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/gnerf-gan-based-neural-radiance-field-without","slug":"gnerf-gan-based-neural-radiance-field-without","title":"GNeRF: GAN-based Neural Radiance Field without Posed Camera","date":"2021-03-29","arxiv_id":"2103.15606","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":2,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/gnerf-gan-based-neural-radiance-field-without#ran","syntology_url":"https://syntology.ai/paper/2103.15606","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.15606"}},"official":{"repos":["quan-meng/gnerf"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/nemi-unifying-neural-radiance-fields-with","slug":"nemi-unifying-neural-radiance-fields-with","title":"MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis","date":"2021-03-27","arxiv_id":"2103.14910","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":0,"n_instrument":5,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"5 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; 5 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/nemi-unifying-neural-radiance-fields-with#ran","syntology_url":"https://syntology.ai/paper/2103.14910","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.14910"}},"official":{"repos":["vincentfung13/MINE"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/kilonerf-speeding-up-neural-radiance-fields","slug":"kilonerf-speeding-up-neural-radiance-fields","title":"KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs","date":"2021-03-25","arxiv_id":"2103.13744","repositories_listed":4,"syntology":{"n":7,"n_ran":7,"n_constructed":1,"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 1 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/kilonerf-speeding-up-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2103.13744","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.13744"}},"official":{"repos":["creiser/kilonerf"],"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/plenoctrees-for-real-time-rendering-of-neural","slug":"plenoctrees-for-real-time-rendering-of-neural","title":"PlenOctrees for Real-time Rendering of Neural Radiance Fields","date":"2021-03-25","arxiv_id":"2103.14024","repositories_listed":5,"syntology":{"n":13,"n_ran":10,"n_constructed":3,"n_ran_checked":7,"n_instrument":3,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"10 ran (of which 3 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) · 3 unverified","sample_list":"/paper/plenoctrees-for-real-time-rendering-of-neural#ran","syntology_url":"https://syntology.ai/paper/2103.14024","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.14024"}},"official":{"repos":["sxyu/plenoctree"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/mip-nerf-a-multiscale-representation-for-anti","slug":"mip-nerf-a-multiscale-representation-for-anti","title":"Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields","date":"2021-03-24","arxiv_id":"2103.13415","repositories_listed":4,"syntology":{"n":33,"n_ran":22,"n_constructed":2,"n_ran_checked":15,"n_instrument":7,"n_unverified":11,"n_honours":0,"n_violates":1,"n_no_contract":14,"n_pointer_only":13,"phrase":"22 ran (of which 2 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 1 violated, 14 with no contract checked; 7 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/mip-nerf-a-multiscale-representation-for-anti#ran","syntology_url":"https://syntology.ai/paper/2103.13415","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.13415"}},"official":{"repos":["google/mipnerf"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/ad-nerf-audio-driven-neural-radiance-fields","slug":"ad-nerf-audio-driven-neural-radiance-fields","title":"AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis","date":"2021-03-20","arxiv_id":"2103.11078","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"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 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/ad-nerf-audio-driven-neural-radiance-fields#ran","syntology_url":"https://syntology.ai/paper/2103.11078","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.11078"}},"official":{"repos":["YudongGuo/AD-NeRF"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-neural-radiance-fields-without-known","slug":"nerf-neural-radiance-fields-without-known","title":"NeRF--: Neural Radiance Fields Without Known Camera Parameters","date":"2021-02-14","arxiv_id":"2102.07064","repositories_listed":5,"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":2,"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/nerf-neural-radiance-fields-without-known#ran","syntology_url":"https://syntology.ai/paper/2102.07064","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.07064"}},"official":{"repos":["ActiveVisionLab/nerfmm"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"url":"/paper/pixelnerf-neural-radiance-fields-from-one-or","slug":"pixelnerf-neural-radiance-fields-from-one-or","title":"pixelNeRF: Neural Radiance Fields from One or Few Images","date":"2020-12-03","arxiv_id":"2012.02190","repositories_listed":2,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":0,"n_instrument":6,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"6 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; 6 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pixelnerf-neural-radiance-fields-from-one-or#ran","syntology_url":"https://syntology.ai/paper/2012.02190","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.02190"}},"official":{"repos":["sxyu/pixel-nerf"],"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/nerf-analyzing-and-improving-neural-radiance","slug":"nerf-analyzing-and-improving-neural-radiance","title":"NeRF++: Analyzing and Improving Neural Radiance Fields","date":"2020-10-15","arxiv_id":"2010.07492","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":1,"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: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/nerf-analyzing-and-improving-neural-radiance#ran","syntology_url":"https://syntology.ai/paper/2010.07492","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.07492"}},"official":{"repos":["Kai-46/nerfplusplus"],"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/nerf-in-the-wild-neural-radiance-fields-for","slug":"nerf-in-the-wild-neural-radiance-fields-for","title":"NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections","date":"2020-08-05","arxiv_id":"2008.02268","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/nerf-in-the-wild-neural-radiance-fields-for#ran","syntology_url":"https://syntology.ai/paper/2008.02268","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.02268"}},"official":null}},{"url":"/paper/neural-sparse-voxel-fields","slug":"neural-sparse-voxel-fields","title":"Neural Sparse Voxel Fields","date":"2020-07-22","arxiv_id":"2007.11571","repositories_listed":1,"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":3,"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/neural-sparse-voxel-fields#ran","syntology_url":"https://syntology.ai/paper/2007.11571","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.11571"}},"official":{"repos":["facebookresearch/NSVF"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/nerf-representing-scenes-as-neural-radiance","slug":"nerf-representing-scenes-as-neural-radiance","title":"NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis","date":"2020-03-19","arxiv_id":"2003.08934","repositories_listed":37,"syntology":{"n":56,"n_ran":44,"n_constructed":0,"n_ran_checked":24,"n_instrument":20,"n_unverified":12,"n_honours":1,"n_violates":1,"n_no_contract":22,"n_pointer_only":6,"phrase":"44 ran (of which 0 constructed an object rather than computing a result; 24 with no instrument failure: 1 honoured, 1 violated, 22 with no contract checked; 20 where Syntology's instrument failed) · 12 unverified","sample_list":"/paper/nerf-representing-scenes-as-neural-radiance#ran","syntology_url":"https://syntology.ai/paper/2003.08934","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.08934"}},"official":{"repos":["bmild/nerf"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["listed","official","unlocated"]}}}],"record_sha256":"7451b2351dba4428cd968b8d0252828150a370fe7362777e4905c2c5eeb4affb","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}