{"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/video-generation/papers/ran/3","list_of":"/task/video-generation","task":"Video Generation","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":[201,257],"of":257,"counts":{"archive_papers_tagged":1466,"with_a_code_link":609,"where_syntology_ran_a_sample":257,"not_listed_spam_title":0,"listed":1466,"listed_where_code_ran":257,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":221,"every_run_a_failure_of_syntologys_instrument":36,"listed_with_a_run_with_no_instrument_failure":221,"listed_every_run_a_failure_of_syntologys_instrument":36,"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/video-generation/papers/ran/1","prev":"/task/video-generation/papers/ran/2","next":null,"papers":[{"url":"/paper/bidirectionally-deformable-motion-modulation","slug":"bidirectionally-deformable-motion-modulation","title":"Bidirectionally Deformable Motion Modulation For Video-based Human Pose Transfer","date":"2023-07-15","arxiv_id":"2307.07754","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":4,"n_ran_checked":4,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"5 ran (of which 4 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) · 0 unverified","sample_list":"/paper/bidirectionally-deformable-motion-modulation#ran","syntology_url":"https://syntology.ai/paper/2307.07754","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07754"}},"official":{"repos":["rocketappslab/bdmm"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/ddlp-unsupervised-object-centric-video","slug":"ddlp-unsupervised-object-centric-video","title":"DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles","date":"2023-06-09","arxiv_id":"2306.05957","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":2,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 2 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ddlp-unsupervised-object-centric-video#ran","syntology_url":"https://syntology.ai/paper/2306.05957","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.05957"}},"official":{"repos":["taldatech/ddlp"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/video-diffusion-models-with-local-global","slug":"video-diffusion-models-with-local-global","title":"Video Diffusion Models with Local-Global Context Guidance","date":"2023-06-05","arxiv_id":"2306.02562","repositories_listed":1,"syntology":{"n":17,"n_ran":16,"n_constructed":0,"n_ran_checked":16,"n_instrument":0,"n_unverified":1,"n_honours":2,"n_violates":3,"n_no_contract":11,"n_pointer_only":3,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 16 with no instrument failure: 2 honoured, 3 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/video-diffusion-models-with-local-global#ran","syntology_url":"https://syntology.ai/paper/2306.02562","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02562"}},"official":{"repos":["exisas/lgc-vd"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":16,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/gen-l-video-multi-text-to-long-video","slug":"gen-l-video-multi-text-to-long-video","title":"Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising","date":"2023-05-29","arxiv_id":"2305.18264","repositories_listed":1,"syntology":{"n":8,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":5,"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) · 5 unverified","sample_list":"/paper/gen-l-video-multi-text-to-long-video#ran","syntology_url":"https://syntology.ai/paper/2305.18264","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.18264"}},"official":{"repos":["g-u-n/gen-l-video"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/large-language-models-are-frame-level","slug":"large-language-models-are-frame-level","title":"DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation","date":"2023-05-23","arxiv_id":"2305.14330","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/large-language-models-are-frame-level#ran","syntology_url":"https://syntology.ai/paper/2305.14330","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.14330"}},"official":{"repos":["ku-cvlab/direct2v"],"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/controlvideo-training-free-controllable-text","slug":"controlvideo-training-free-controllable-text","title":"ControlVideo: Training-free Controllable Text-to-Video Generation","date":"2023-05-22","arxiv_id":"2305.13077","repositories_listed":1,"syntology":{"n":9,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"3 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; 1 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/controlvideo-training-free-controllable-text#ran","syntology_url":"https://syntology.ai/paper/2305.13077","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.13077"}},"official":{"repos":["ybybzhang/controlvideo"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/vdt-an-empirical-study-on-video-diffusion","slug":"vdt-an-empirical-study-on-video-diffusion","title":"VDT: General-purpose Video Diffusion Transformers via Mask Modeling","date":"2023-05-22","arxiv_id":"2305.13311","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":4,"n_instrument":4,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":2,"n_pointer_only":9,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 0 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/vdt-an-empirical-study-on-video-diffusion#ran","syntology_url":"https://syntology.ai/paper/2305.13311","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.13311"}},"official":{"repos":["rerv/vdt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/styleavatar-real-time-photo-realistic","slug":"styleavatar-real-time-photo-realistic","title":"StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video","date":"2023-05-01","arxiv_id":"2305.00942","repositories_listed":1,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/styleavatar-real-time-photo-realistic#ran","syntology_url":"https://syntology.ai/paper/2305.00942","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.00942"}},"official":{"repos":["lizhenwangt/styleavatar"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/align-your-latents-high-resolution-video","slug":"align-your-latents-high-resolution-video","title":"Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models","date":"2023-04-18","arxiv_id":"2304.08818","repositories_listed":4,"syntology":{"n":26,"n_ran":18,"n_constructed":0,"n_ran_checked":12,"n_instrument":6,"n_unverified":8,"n_honours":2,"n_violates":3,"n_no_contract":7,"n_pointer_only":3,"phrase":"18 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 2 honoured, 3 violated, 7 with no contract checked; 6 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/align-your-latents-high-resolution-video#ran","syntology_url":"https://syntology.ai/paper/2304.08818","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.08818"}},"official":{"repos":["stability-ai/generative-models"],"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":["found_in_text","listed","unlocated"]}}},{"url":"/paper/follow-your-pose-pose-guided-text-to-video","slug":"follow-your-pose-pose-guided-text-to-video","title":"Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videos","date":"2023-04-03","arxiv_id":"2304.01186","repositories_listed":2,"syntology":{"n":10,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":6,"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) · 6 unverified","sample_list":"/paper/follow-your-pose-pose-guided-text-to-video#ran","syntology_url":"https://syntology.ai/paper/2304.01186","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.01186"}},"official":{"repos":["mayuelala/followyourpose"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/fine-grained-audible-video-description","slug":"fine-grained-audible-video-description","title":"Fine-grained Audible Video Description","date":"2023-03-27","arxiv_id":"2303.15616","repositories_listed":1,"syntology":{"n":12,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"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) · 5 unverified","sample_list":"/paper/fine-grained-audible-video-description#ran","syntology_url":"https://syntology.ai/paper/2303.15616","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.15616"}},"official":{"repos":["opennlplab/favdbench"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/conditional-image-to-video-generation-with","slug":"conditional-image-to-video-generation-with","title":"Conditional Image-to-Video Generation with Latent Flow Diffusion Models","date":"2023-03-24","arxiv_id":"2303.13744","repositories_listed":1,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":4,"n_no_contract":1,"n_pointer_only":2,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 4 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/conditional-image-to-video-generation-with#ran","syntology_url":"https://syntology.ai/paper/2303.13744","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.13744"}},"official":{"repos":["nihaomiao/cvpr23_lfdm"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/blind-video-deflickering-by-neural-filtering","slug":"blind-video-deflickering-by-neural-filtering","title":"Blind Video Deflickering by Neural Filtering with a Flawed Atlas","date":"2023-03-14","arxiv_id":"2303.08120","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/blind-video-deflickering-by-neural-filtering#ran","syntology_url":"https://syntology.ai/paper/2303.08120","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.08120"}},"official":{"repos":["chenyanglei/all-in-one-deflicker"],"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/consistency-models","slug":"consistency-models","title":"Consistency Models","date":"2023-03-02","arxiv_id":"2303.01469","repositories_listed":15,"syntology":{"n":57,"n_ran":32,"n_constructed":5,"n_ran_checked":22,"n_instrument":10,"n_unverified":25,"n_honours":5,"n_violates":3,"n_no_contract":14,"n_pointer_only":18,"phrase":"32 ran (of which 5 constructed an object rather than computing a result; 22 with no instrument failure: 5 honoured, 3 violated, 14 with no contract checked; 10 where Syntology's instrument failed) · 25 unverified","sample_list":"/paper/consistency-models#ran","syntology_url":"https://syntology.ai/paper/2303.01469","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.01469"}},"official":{"repos":["openai/consistency_models"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":9,"ran_from_kinds":["listed","official","unlocated"]}}},{"url":"/paper/video-probabilistic-diffusion-models-in","slug":"video-probabilistic-diffusion-models-in","title":"Video Probabilistic Diffusion Models in Projected Latent Space","date":"2023-02-15","arxiv_id":"2302.07685","repositories_listed":1,"syntology":{"n":8,"n_ran":4,"n_constructed":2,"n_ran_checked":4,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 2 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) · 4 unverified","sample_list":"/paper/video-probabilistic-diffusion-models-in#ran","syntology_url":"https://syntology.ai/paper/2302.07685","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.07685"}},"official":null}},{"url":"/paper/make-an-audio-text-to-audio-generation-with","slug":"make-an-audio-text-to-audio-generation-with","title":"Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models","date":"2023-01-30","arxiv_id":"2301.12661","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/make-an-audio-text-to-audio-generation-with#ran","syntology_url":"https://syntology.ai/paper/2301.12661","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2301.12661"}},"official":null}},{"url":"/paper/tune-a-video-one-shot-tuning-of-image","slug":"tune-a-video-one-shot-tuning-of-image","title":"Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation","date":"2022-12-22","arxiv_id":"2212.11565","repositories_listed":3,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/tune-a-video-one-shot-tuning-of-image#ran","syntology_url":"https://syntology.ai/paper/2212.11565","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.11565"}},"official":{"repos":["showlab/Tune-A-Video"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/scalable-adaptive-computation-for-iterative","slug":"scalable-adaptive-computation-for-iterative","title":"Scalable Adaptive Computation for Iterative Generation","date":"2022-12-22","arxiv_id":"2212.11972","repositories_listed":2,"syntology":{"n":29,"n_ran":21,"n_constructed":9,"n_ran_checked":18,"n_instrument":3,"n_unverified":8,"n_honours":8,"n_violates":0,"n_no_contract":10,"n_pointer_only":1,"phrase":"21 ran (of which 9 constructed an object rather than computing a result; 18 with no instrument failure: 8 honoured, 0 violated, 10 with no contract checked; 3 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/scalable-adaptive-computation-for-iterative#ran","syntology_url":"https://syntology.ai/paper/2212.11972","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.11972"}},"official":{"repos":["google-research/pix2seq"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":2,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/seqdiffuseq-text-diffusion-with-encoder","slug":"seqdiffuseq-text-diffusion-with-encoder","title":"SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers","date":"2022-12-20","arxiv_id":"2212.10325","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":3,"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; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/seqdiffuseq-text-diffusion-with-encoder#ran","syntology_url":"https://syntology.ai/paper/2212.10325","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.10325"}},"official":{"repos":["yuanhy1997/seqdiffuseq"],"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","unlocated"]}}},{"url":"/paper/mm-diffusion-learning-multi-modal-diffusion","slug":"mm-diffusion-learning-multi-modal-diffusion","title":"MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation","date":"2022-12-19","arxiv_id":"2212.09478","repositories_listed":1,"syntology":{"n":18,"n_ran":16,"n_constructed":0,"n_ran_checked":12,"n_instrument":4,"n_unverified":2,"n_honours":3,"n_violates":0,"n_no_contract":9,"n_pointer_only":8,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 3 honoured, 0 violated, 9 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mm-diffusion-learning-multi-modal-diffusion#ran","syntology_url":"https://syntology.ai/paper/2212.09478","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.09478"}},"official":{"repos":["researchmm/mm-diffusion"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/magvit-masked-generative-video-transformer","slug":"magvit-masked-generative-video-transformer","title":"MAGVIT: Masked Generative Video Transformer","date":"2022-12-10","arxiv_id":"2212.05199","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":0,"n_no_contract":9,"n_pointer_only":1,"phrase":"10 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/magvit-masked-generative-video-transformer#ran","syntology_url":"https://syntology.ai/paper/2212.05199","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.05199"}},"official":{"repos":["google-research/magvit"],"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/vidm-video-implicit-diffusion-models","slug":"vidm-video-implicit-diffusion-models","title":"VIDM: Video Implicit Diffusion Models","date":"2022-12-01","arxiv_id":"2212.00235","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/vidm-video-implicit-diffusion-models#ran","syntology_url":"https://syntology.ai/paper/2212.00235","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.00235"}},"official":{"repos":["MKFMIKU/VIDM"],"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/videoretalking-audio-based-lip","slug":"videoretalking-audio-based-lip","title":"VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild","date":"2022-11-27","arxiv_id":"2211.14758","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":4,"n_pointer_only":1,"phrase":"6 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/videoretalking-audio-based-lip#ran","syntology_url":"https://syntology.ai/paper/2211.14758","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.14758"}},"official":null}},{"url":"/paper/latent-video-diffusion-models-for-high","slug":"latent-video-diffusion-models-for-high","title":"Latent Video Diffusion Models for High-Fidelity Long Video Generation","date":"2022-11-23","arxiv_id":"2211.13221","repositories_listed":1,"syntology":{"n":14,"n_ran":13,"n_constructed":0,"n_ran_checked":7,"n_instrument":6,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":5,"n_pointer_only":5,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 1 violated, 5 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/latent-video-diffusion-models-for-high#ran","syntology_url":"https://syntology.ai/paper/2211.13221","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.13221"}},"official":{"repos":["yingqinghe/lvdm"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/sinfusion-training-diffusion-models-on-a","slug":"sinfusion-training-diffusion-models-on-a","title":"SinFusion: Training Diffusion Models on a Single Image or Video","date":"2022-11-21","arxiv_id":"2211.11743","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":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/sinfusion-training-diffusion-models-on-a#ran","syntology_url":"https://syntology.ai/paper/2211.11743","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.11743"}},"official":{"repos":["yanivnik/sinfusion-code"],"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/disentangling-aesthetic-and-technical-effects","slug":"disentangling-aesthetic-and-technical-effects","title":"Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives","date":"2022-11-09","arxiv_id":"2211.04894","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":3,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 3 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/disentangling-aesthetic-and-technical-effects#ran","syntology_url":"https://syntology.ai/paper/2211.04894","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.04894"}},"official":{"repos":["vqassessment/dover","QualityAssessment/DOVER"],"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/phenaki-variable-length-video-generation-from","slug":"phenaki-variable-length-video-generation-from","title":"Phenaki: Variable Length Video Generation From Open Domain Textual Description","date":"2022-10-05","arxiv_id":"2210.02399","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":2,"n_no_contract":0,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 2 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/phenaki-variable-length-video-generation-from#ran","syntology_url":"https://syntology.ai/paper/2210.02399","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.02399"}},"official":null}},{"url":"/paper/3d-aware-video-generation","slug":"3d-aware-video-generation","title":"3D-Aware Video Generation","date":"2022-06-29","arxiv_id":"2206.14797","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/3d-aware-video-generation#ran","syntology_url":"https://syntology.ai/paper/2206.14797","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.14797"}},"official":{"repos":["sherwinbahmani/3dvideogeneration"],"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/diffusion-models-for-video-prediction-and","slug":"diffusion-models-for-video-prediction-and","title":"Diffusion Models for Video Prediction and Infilling","date":"2022-06-15","arxiv_id":"2206.07696","repositories_listed":1,"syntology":{"n":19,"n_ran":12,"n_constructed":0,"n_ran_checked":8,"n_instrument":4,"n_unverified":7,"n_honours":4,"n_violates":0,"n_no_contract":4,"n_pointer_only":11,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 4 honoured, 0 violated, 4 with no contract checked; 4 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/diffusion-models-for-video-prediction-and#ran","syntology_url":"https://syntology.ai/paper/2206.07696","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.07696"}},"official":{"repos":["Tobi-r9/RaMViD"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/generating-long-videos-of-dynamic-scenes","slug":"generating-long-videos-of-dynamic-scenes","title":"Generating Long Videos of Dynamic Scenes","date":"2022-06-07","arxiv_id":"2206.03429","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/generating-long-videos-of-dynamic-scenes#ran","syntology_url":"https://syntology.ai/paper/2206.03429","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.03429"}},"official":null}},{"url":"/paper/masked-conditional-video-diffusion-for","slug":"masked-conditional-video-diffusion-for","title":"MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation","date":"2022-05-19","arxiv_id":"2205.09853","repositories_listed":2,"syntology":{"n":16,"n_ran":7,"n_constructed":1,"n_ran_checked":4,"n_instrument":3,"n_unverified":9,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"7 ran (of which 1 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/masked-conditional-video-diffusion-for#ran","syntology_url":"https://syntology.ai/paper/2205.09853","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.09853"}},"official":{"repos":["voletiv/mcvd-pytorch"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/video-diffusion-models","slug":"video-diffusion-models","title":"Video Diffusion Models","date":"2022-04-07","arxiv_id":"2204.03458","repositories_listed":5,"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/video-diffusion-models#ran","syntology_url":"https://syntology.ai/paper/2204.03458","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.03458"}},"official":null}},{"url":"/paper/diffusion-probabilistic-modeling-for-video","slug":"diffusion-probabilistic-modeling-for-video","title":"Diffusion Probabilistic Modeling for Video Generation","date":"2022-03-16","arxiv_id":"2203.09481","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":3,"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; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/diffusion-probabilistic-modeling-for-video#ran","syntology_url":"https://syntology.ai/paper/2203.09481","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09481"}},"official":{"repos":["buggyyang/rvd"],"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/depth-aware-generative-adversarial-network","slug":"depth-aware-generative-adversarial-network","title":"Depth-Aware Generative Adversarial Network for Talking Head Video Generation","date":"2022-03-13","arxiv_id":"2203.06605","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"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) · 3 unverified","sample_list":"/paper/depth-aware-generative-adversarial-network#ran","syntology_url":"https://syntology.ai/paper/2203.06605","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.06605"}},"official":{"repos":["harlanhong/cvpr2022-dagan"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/styleheat-one-shot-high-resolution-editable","slug":"styleheat-one-shot-high-resolution-editable","title":"StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN","date":"2022-03-08","arxiv_id":"2203.04036","repositories_listed":1,"syntology":{"n":8,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"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) · 4 unverified","sample_list":"/paper/styleheat-one-shot-high-resolution-editable#ran","syntology_url":"https://syntology.ai/paper/2203.04036","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.04036"}},"official":{"repos":["FeiiYin/StyleHEAT"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/benchmarking-generative-latent-variable","slug":"benchmarking-generative-latent-variable","title":"Benchmarking Generative Latent Variable Models for Speech","date":"2022-02-22","arxiv_id":"2202.12707","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/benchmarking-generative-latent-variable#ran","syntology_url":"https://syntology.ai/paper/2202.12707","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.12707"}},"official":{"repos":["jakobhavtorn/benchmarking-lvms"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/make-it-move-controllable-image-to-video","slug":"make-it-move-controllable-image-to-video","title":"Make It Move: Controllable Image-to-Video Generation with Text Descriptions","date":"2021-12-06","arxiv_id":"2112.02815","repositories_listed":1,"syntology":{"n":13,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":6,"n_honours":0,"n_violates":3,"n_no_contract":3,"n_pointer_only":1,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 3 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/make-it-move-controllable-image-to-video#ran","syntology_url":"https://syntology.ai/paper/2112.02815","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.02815"}},"official":{"repos":["youncy-hu/mage"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/nuwa-visual-synthesis-pre-training-for-neural","slug":"nuwa-visual-synthesis-pre-training-for-neural","title":"NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion","date":"2021-11-24","arxiv_id":"2111.12417","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":3,"n_no_contract":0,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 3 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/nuwa-visual-synthesis-pre-training-for-neural#ran","syntology_url":"https://syntology.ai/paper/2111.12417","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12417"}},"official":null}},{"url":"/paper/diverse-generation-from-a-single-video-made","slug":"diverse-generation-from-a-single-video-made","title":"Diverse Generation from a Single Video Made Possible","date":"2021-09-17","arxiv_id":"2109.08591","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/diverse-generation-from-a-single-video-made#ran","syntology_url":"https://syntology.ai/paper/2109.08591","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.08591"}},"official":{"repos":["nivha/single_video_generation"],"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","unlocated"]}}},{"url":"/paper/slamp-stochastic-latent-appearance-and-motion","slug":"slamp-stochastic-latent-appearance-and-motion","title":"SLAMP: Stochastic Latent Appearance and Motion Prediction","date":"2021-08-05","arxiv_id":"2108.02760","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/slamp-stochastic-latent-appearance-and-motion#ran","syntology_url":"https://syntology.ai/paper/2108.02760","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02760"}},"official":{"repos":["kaanakan/slamp"],"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/ccvs-context-aware-controllable-video","slug":"ccvs-context-aware-controllable-video","title":"CCVS: Context-aware Controllable Video Synthesis","date":"2021-07-16","arxiv_id":"2107.08037","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":1,"phrase":"7 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/ccvs-context-aware-controllable-video#ran","syntology_url":"https://syntology.ai/paper/2107.08037","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.08037"}},"official":{"repos":["16lemoing/ccvs"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/fitvid-overfitting-in-pixel-level-video","slug":"fitvid-overfitting-in-pixel-level-video","title":"FitVid: Overfitting in Pixel-Level Video Prediction","date":"2021-06-24","arxiv_id":"2106.13195","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/fitvid-overfitting-in-pixel-level-video#ran","syntology_url":"https://syntology.ai/paper/2106.13195","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2106.13195"}},"official":{"repos":["google-research/fitvid"],"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/latent-neural-differential-equations-for","slug":"latent-neural-differential-equations-for","title":"Latent Neural Differential Equations for Video Generation","date":"2020-11-07","arxiv_id":"2011.03864","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/latent-neural-differential-equations-for#ran","syntology_url":"https://syntology.ai/paper/2011.03864","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2011.03864"}},"official":{"repos":["Zasder3/Latent-Neural-Differential-Equations-for-Video-Generation"],"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/compositional-video-synthesis-with-action","slug":"compositional-video-synthesis-with-action","title":"Compositional Video Synthesis with Action Graphs","date":"2020-06-27","arxiv_id":"2006.15327","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"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) · 2 unverified","sample_list":"/paper/compositional-video-synthesis-with-action#ran","syntology_url":"https://syntology.ai/paper/2006.15327","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.15327"}},"official":{"repos":["roeiherz/AG2Video"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/hierarchical-patch-vae-gan-generating-diverse","slug":"hierarchical-patch-vae-gan-generating-diverse","title":"Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample","date":"2020-06-22","arxiv_id":"2006.12226","repositories_listed":3,"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/hierarchical-patch-vae-gan-generating-diverse#ran","syntology_url":"https://syntology.ai/paper/2006.12226","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.12226"}},"official":{"repos":["shirgur/hp-vae-gan"],"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":["official"]}}},{"url":"/paper/latent-video-transformer","slug":"latent-video-transformer","title":"Latent Video Transformer","date":"2020-06-18","arxiv_id":"2006.10704","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/latent-video-transformer#ran","syntology_url":"https://syntology.ai/paper/2006.10704","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.10704"}},"official":{"repos":["rakhimovv/lvt"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/audio-driven-talking-face-video-generation","slug":"audio-driven-talking-face-video-generation","title":"Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose","date":"2020-02-24","arxiv_id":"2002.10137","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/audio-driven-talking-face-video-generation#ran","syntology_url":"https://syntology.ai/paper/2002.10137","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.10137"}},"official":{"repos":["yiranran/Audio-driven-TalkingFace-HeadPose"],"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/stochastic-latent-residual-video-prediction-1","slug":"stochastic-latent-residual-video-prediction-1","title":"Stochastic Latent Residual Video Prediction","date":"2020-02-21","arxiv_id":"2002.09219","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"phrase":"10 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; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/stochastic-latent-residual-video-prediction-1#ran","syntology_url":"https://syntology.ai/paper/2002.09219","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.09219"}},"official":{"repos":["edouardelasalles/srvp"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["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/tganv2-efficient-training-of-large-models-for","slug":"tganv2-efficient-training-of-large-models-for","title":"Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN","date":"2018-11-22","arxiv_id":"1811.09245","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"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, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/tganv2-efficient-training-of-large-models-for#ran","syntology_url":"https://syntology.ai/paper/1811.09245","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.09245"}},"official":{"repos":["pfnet-research/tgan2"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/everybody-dance-now","slug":"everybody-dance-now","title":"Everybody Dance Now","date":"2018-08-22","arxiv_id":"1808.07371","repositories_listed":14,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/everybody-dance-now#ran","syntology_url":"https://syntology.ai/paper/1808.07371","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1808.07371"}},"official":{"repos":["carolineec/EverybodyDanceNow"],"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-to-forecast-and-refine-residual","slug":"learning-to-forecast-and-refine-residual","title":"Learning to Forecast and Refine Residual Motion for Image-to-Video Generation","date":"2018-07-26","arxiv_id":"1807.09951","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/learning-to-forecast-and-refine-residual#ran","syntology_url":"https://syntology.ai/paper/1807.09951","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.09951"}},"official":null}},{"url":"/paper/stochastic-adversarial-video-prediction","slug":"stochastic-adversarial-video-prediction","title":"Stochastic Adversarial Video Prediction","date":"2018-04-04","arxiv_id":"1804.01523","repositories_listed":4,"syntology":{"n":16,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":6,"n_honours":0,"n_violates":1,"n_no_contract":6,"n_pointer_only":3,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 3 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/stochastic-adversarial-video-prediction#ran","syntology_url":"https://syntology.ai/paper/1804.01523","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.01523"}},"official":{"repos":["alexlee-gk/video_prediction"],"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":["listed","official"]}}},{"url":"/paper/stochastic-video-generation-with-a-learned","slug":"stochastic-video-generation-with-a-learned","title":"Stochastic Video Generation with a Learned Prior","date":"2018-02-21","arxiv_id":"1802.07687","repositories_listed":3,"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":2,"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/stochastic-video-generation-with-a-learned#ran","syntology_url":"https://syntology.ai/paper/1802.07687","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1802.07687"}},"official":{"repos":["edenton/svg"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/gans-trained-by-a-two-time-scale-update-rule","slug":"gans-trained-by-a-two-time-scale-update-rule","title":"GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium","date":"2017-06-26","arxiv_id":"1706.08500","repositories_listed":71,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/gans-trained-by-a-two-time-scale-update-rule#ran","syntology_url":"https://syntology.ai/paper/1706.08500","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1706.08500"}},"official":{"repos":["bioinf-jku/TTUR"],"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/temporal-generative-adversarial-nets-with","slug":"temporal-generative-adversarial-nets-with","title":"Temporal Generative Adversarial Nets with Singular Value Clipping","date":"2016-11-21","arxiv_id":"1611.06624","repositories_listed":4,"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/temporal-generative-adversarial-nets-with#ran","syntology_url":"https://syntology.ai/paper/1611.06624","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1611.06624"}},"official":null}},{"url":"/paper/unsupervised-learning-for-physical","slug":"unsupervised-learning-for-physical","title":"Unsupervised Learning for Physical Interaction through Video Prediction","date":"2016-05-23","arxiv_id":"1605.07157","repositories_listed":2,"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":2,"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/unsupervised-learning-for-physical#ran","syntology_url":"https://syntology.ai/paper/1605.07157","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1605.07157"}},"official":null}}],"record_sha256":"92a9676255e1c88f3696fcc87cbcd6f540057705a524c7ba2d8b3dc9b65c16fc","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}