{"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/3d-human-pose-estimation/papers/3","list_of":"/task/3d-human-pose-estimation","task":"3D Human Pose Estimation","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":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":7,"rows_per_page":100,"rows":[201,300],"of":665,"counts":{"archive_papers_tagged":665,"with_a_code_link":353,"where_syntology_ran_a_sample":94,"not_listed_spam_title":0,"listed":665,"listed_where_code_ran":94,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":80,"every_run_a_failure_of_syntologys_instrument":14,"listed_with_a_run_with_no_instrument_failure":80,"listed_every_run_a_failure_of_syntologys_instrument":14,"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/3d-human-pose-estimation","prev":"/task/3d-human-pose-estimation/papers/2","next":"/task/3d-human-pose-estimation/papers/4","papers":[{"url":"/paper/learning-to-estimate-external-forces-of-human","slug":"learning-to-estimate-external-forces-of-human","title":"Learning to Estimate External Forces of Human Motion in Video","date":"2022-07-12","arxiv_id":"2207.05845","repositories_listed":1,"syntology":null},{"url":"/paper/occluded-human-body-capture-with-self","slug":"occluded-human-body-capture-with-self","title":"Occluded Human Body Capture with Self-Supervised Spatial-Temporal Motion Prior","date":"2022-07-12","arxiv_id":"2207.05375","repositories_listed":1,"syntology":null},{"url":"/paper/graphmlp-a-graph-mlp-like-architecture-for-3d","slug":"graphmlp-a-graph-mlp-like-architecture-for-3d","title":"GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose Estimation","date":"2022-06-13","arxiv_id":"2206.06420","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":0,"n_no_contract":5,"n_pointer_only":1,"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) · 4 unverified","sample_list":"/paper/graphmlp-a-graph-mlp-like-architecture-for-3d#ran","syntology_url":"https://syntology.ai/paper/2206.06420","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.06420"}},"official":{"repos":["vegetebird/graphmlp"],"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/efficient-human-pose-estimation-via-3d-event","slug":"efficient-human-pose-estimation-via-3d-event","title":"Efficient Human Pose Estimation via 3D Event Point Cloud","date":"2022-06-09","arxiv_id":"2206.04511","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":3,"n_instrument":4,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/efficient-human-pose-estimation-via-3d-event#ran","syntology_url":"https://syntology.ai/paper/2206.04511","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.04511"}},"official":{"repos":["masterhow/eventpointpose"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/heater-an-efficient-and-unified-network-for","slug":"heater-an-efficient-and-unified-network-for","title":"FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER","date":"2022-05-30","arxiv_id":"2205.15448","repositories_listed":1,"syntology":null},{"url":"/paper/dual-networks-based-3d-multi-person-pose","slug":"dual-networks-based-3d-multi-person-pose","title":"Dual networks based 3D Multi-Person Pose Estimation from Monocular Video","date":"2022-05-02","arxiv_id":"2205.00748","repositories_listed":1,"syntology":null},{"url":"/paper/pedrecnet-multi-task-deep-neural-network-for","slug":"pedrecnet-multi-task-deep-neural-network-for","title":"PedRecNet: Multi-task deep neural network for full 3D human pose and orientation estimation","date":"2022-04-25","arxiv_id":"2204.11548","repositories_listed":1,"syntology":null},{"url":"/paper/not-all-tokens-are-equal-human-centric-visual","slug":"not-all-tokens-are-equal-human-centric-visual","title":"Not All Tokens Are Equal: Human-centric Visual Analysis via Token Clustering Transformer","date":"2022-04-19","arxiv_id":"2204.08680","repositories_listed":1,"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/not-all-tokens-are-equal-human-centric-visual#ran","syntology_url":"https://syntology.ai/paper/2204.08680","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.08680"}},"official":{"repos":["zengwang430521/tcformer"],"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/posetriplet-co-evolving-3d-human-pose","slug":"posetriplet-co-evolving-3d-human-pose","title":"PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision","date":"2022-03-29","arxiv_id":"2203.15625","repositories_listed":1,"syntology":null},{"url":"/paper/crossformer-cross-spatio-temporal-transformer","slug":"crossformer-cross-spatio-temporal-transformer","title":"CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose Estimation","date":"2022-03-24","arxiv_id":"2203.13387","repositories_listed":1,"syntology":null},{"url":"/paper/ray3d-ray-based-3d-human-pose-estimation-for","slug":"ray3d-ray-based-3d-human-pose-estimation-for","title":"Ray3D: ray-based 3D human pose estimation for monocular absolute 3D localization","date":"2022-03-22","arxiv_id":"2203.11471","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 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; 0 where Syntology's instrument failed) · 1 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/ray3d-ray-based-3d-human-pose-estimation-for#ran","syntology_url":"https://syntology.ai/paper/2203.11471","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.11471"}},"official":{"repos":["YxZhxn/Ray3D"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/hsc4d-human-centered-4d-scene-capture-in","slug":"hsc4d-human-centered-4d-scene-capture-in","title":"HSC4D: Human-centered 4D Scene Capture in Large-scale Indoor-outdoor Space Using Wearable IMUs and LiDAR","date":"2022-03-17","arxiv_id":"2203.09215","repositories_listed":1,"syntology":null},{"url":"/paper/deciwatch-a-simple-baseline-for-10x-efficient","slug":"deciwatch-a-simple-baseline-for-10x-efficient","title":"DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation","date":"2022-03-16","arxiv_id":"2203.08713","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"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) · 2 unverified","sample_list":"/paper/deciwatch-a-simple-baseline-for-10x-efficient#ran","syntology_url":"https://syntology.ai/paper/2203.08713","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.08713"}},"official":{"repos":["cure-lab/DeciWatch"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/p-stmo-pre-trained-spatial-temporal-many-to","slug":"p-stmo-pre-trained-spatial-temporal-many-to","title":"P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose Estimation","date":"2022-03-15","arxiv_id":"2203.07628","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":6,"n_ran_checked":7,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"phrase":"9 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; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/p-stmo-pre-trained-spatial-temporal-many-to#ran","syntology_url":"https://syntology.ai/paper/2203.07628","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07628"}},"official":{"repos":["patrick-swk/p-stmo"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":6,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/quantification-of-occlusion-handling","slug":"quantification-of-occlusion-handling","title":"Quantification of Occlusion Handling Capability of a 3D Human Pose Estimation Framework","date":"2022-03-08","arxiv_id":"2203.04113","repositories_listed":1,"syntology":null},{"url":"/paper/mixste-seq2seq-mixed-spatio-temporal-encoder","slug":"mixste-seq2seq-mixed-spatio-temporal-encoder","title":"MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video","date":"2022-03-02","arxiv_id":"2203.00859","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":4,"phrase":"4 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; 0 where Syntology's instrument failed) · 0 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/mixste-seq2seq-mixed-spatio-temporal-encoder#ran","syntology_url":"https://syntology.ai/paper/2203.00859","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.00859"}},"official":{"repos":["JinluZhang1126/MixSTE"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/adaptpose-cross-dataset-adaptation-for-3d","slug":"adaptpose-cross-dataset-adaptation-for-3d","title":"AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation","date":"2021-12-22","arxiv_id":"2112.11593","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":1,"n_no_contract":2,"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, 1 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/adaptpose-cross-dataset-adaptation-for-3d#ran","syntology_url":"https://syntology.ai/paper/2112.11593","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.11593"}},"official":{"repos":["mgholamikn/AdaptPose"],"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/elepose-unsupervised-3d-human-pose-estimation","slug":"elepose-unsupervised-3d-human-pose-estimation","title":"ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses","date":"2021-12-14","arxiv_id":"2112.07088","repositories_listed":1,"syntology":null},{"url":"/paper/glamr-global-occlusion-aware-human-mesh","slug":"glamr-global-occlusion-aware-human-mesh","title":"GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras","date":"2021-12-02","arxiv_id":"2112.01524","repositories_listed":1,"syntology":null},{"url":"/paper/camera-distortion-aware-3d-human-pose-1","slug":"camera-distortion-aware-3d-human-pose-1","title":"Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning","date":"2021-11-30","arxiv_id":"2111.15056","repositories_listed":1,"syntology":null},{"url":"/paper/a-lightweight-graph-transformer-network-for","slug":"a-lightweight-graph-transformer-network-for","title":"A Lightweight Graph Transformer Network for Human Mesh Reconstruction from 2D Human Pose","date":"2021-11-24","arxiv_id":"2111.12696","repositories_listed":1,"syntology":null},{"url":"/paper/mhformer-multi-hypothesis-transformer-for-3d","slug":"mhformer-multi-hypothesis-transformer-for-3d","title":"MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation","date":"2021-11-24","arxiv_id":"2111.12707","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"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, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mhformer-multi-hypothesis-transformer-for-3d#ran","syntology_url":"https://syntology.ai/paper/2111.12707","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12707"}},"official":{"repos":["Vegetebird/MHFormer"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/hierarchical-graph-networks-for-3d-human-pose","slug":"hierarchical-graph-networks-for-3d-human-pose","title":"Hierarchical Graph Networks for 3D Human Pose Estimation","date":"2021-11-23","arxiv_id":"2111.11927","repositories_listed":1,"syntology":null},{"url":"/paper/out-of-domain-human-mesh-reconstruction-via","slug":"out-of-domain-human-mesh-reconstruction-via","title":"Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation","date":"2021-11-07","arxiv_id":"2111.04017","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-multi-person-mesh-recovery-from","slug":"dynamic-multi-person-mesh-recovery-from","title":"Dynamic Multi-Person Mesh Recovery From Uncalibrated Multi-View Cameras","date":"2021-10-20","arxiv_id":"2110.10355","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-mocap-data-for-human-mesh-recovery","slug":"leveraging-mocap-data-for-human-mesh-recovery","title":"Leveraging MoCap Data for Human Mesh Recovery","date":"2021-10-18","arxiv_id":"2110.09243","repositories_listed":1,"syntology":null},{"url":"/paper/transfusion-cross-view-fusion-with","slug":"transfusion-cross-view-fusion-with","title":"TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation","date":"2021-10-18","arxiv_id":"2110.09554","repositories_listed":1,"syntology":null},{"url":"/paper/localization-with-sampling-argmax","slug":"localization-with-sampling-argmax","title":"Localization with Sampling-Argmax","date":"2021-10-17","arxiv_id":"2110.08825","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":3,"n_ran_checked":3,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":7,"phrase":"6 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/localization-with-sampling-argmax#ran","syntology_url":"https://syntology.ai/paper/2110.08825","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.08825"}},"official":{"repos":["Jeff-sjtu/sampling-argmax"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/joint-3d-human-shape-recovery-from-a-single","slug":"joint-3d-human-shape-recovery-from-a-single","title":"Joint 3D Human Shape Recovery and Pose Estimation from a Single Image with Bilayer Graph","date":"2021-10-16","arxiv_id":"2110.08472","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-regress-bodies-from-images-using-1","slug":"learning-to-regress-bodies-from-images-using-1","title":"Learning to Regress Bodies from Images using Differentiable Semantic Rendering","date":"2021-10-07","arxiv_id":"2110.03480","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/learning-to-regress-bodies-from-images-using-1#ran","syntology_url":"https://syntology.ai/paper/2110.03480","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.03480"}},"official":{"repos":["saidwivedi/DSR"],"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/hierarchical-kinematic-probability","slug":"hierarchical-kinematic-probability","title":"Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild","date":"2021-10-03","arxiv_id":"2110.00990","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":2,"n_instrument":4,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"6 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; 4 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/hierarchical-kinematic-probability#ran","syntology_url":"https://syntology.ai/paper/2110.00990","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.00990"}},"official":{"repos":["akashsengupta1997/hierarchicalprobabilistic3dhuman"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/spec-seeing-people-in-the-wild-with-an","slug":"spec-seeing-people-in-the-wild-with-an","title":"SPEC: Seeing People in the Wild with an Estimated Camera","date":"2021-10-01","arxiv_id":"2110.00620","repositories_listed":1,"syntology":null},{"url":"/paper/encoder-decoder-with-multi-level-attention","slug":"encoder-decoder-with-multi-level-attention","title":"Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation","date":"2021-09-06","arxiv_id":"2109.02303","repositories_listed":1,"syntology":{"n":18,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/encoder-decoder-with-multi-level-attention#ran","syntology_url":"https://syntology.ai/paper/2109.02303","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.02303"}},"official":{"repos":["ziniuwan/maed"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":8,"ran_from_kinds":["official"]}}},{"url":"/paper/probabilistic-modeling-for-human-mesh","slug":"probabilistic-modeling-for-human-mesh","title":"Probabilistic Modeling for Human Mesh Recovery","date":"2021-08-26","arxiv_id":"2108.11944","repositories_listed":1,"syntology":null},{"url":"/paper/deca-deep-viewpoint-equivariant-human-pose","slug":"deca-deep-viewpoint-equivariant-human-pose","title":"DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders","date":"2021-08-19","arxiv_id":"2108.08557","repositories_listed":1,"syntology":null},{"url":"/paper/sequential-3d-human-pose-estimation-using","slug":"sequential-3d-human-pose-estimation-using","title":"Sequential 3D Human Pose Estimation Using Adaptive Point Cloud Sampling Strategy","date":"2021-08-19","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/self-supervised-3d-human-pose-estimation-with","slug":"self-supervised-3d-human-pose-estimation-with","title":"Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry","date":"2021-08-17","arxiv_id":"2108.07777","repositories_listed":1,"syntology":null},{"url":"/paper/frankmocap-a-monocular-3d-whole-body-pose","slug":"frankmocap-a-monocular-3d-whole-body-pose","title":"FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integration","date":"2021-08-13","arxiv_id":"2108.06428","repositories_listed":1,"syntology":null},{"url":"/paper/metapose-fast-3d-pose-from-multiple-views","slug":"metapose-fast-3d-pose-from-multiple-views","title":"MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision","date":"2021-08-10","arxiv_id":"2108.04869","repositories_listed":1,"syntology":null},{"url":"/paper/lasor-learning-accurate-3d-human-pose-and","slug":"lasor-learning-accurate-3d-human-pose-and","title":"LASOR: Learning Accurate 3D Human Pose and Shape Via Synthetic Occlusion-Aware Data and Neural Mesh Rendering","date":"2021-08-01","arxiv_id":"2108.00351","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"7 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; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/lasor-learning-accurate-3d-human-pose-and#ran","syntology_url":"https://syntology.ai/paper/2108.00351","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.00351"}},"official":{"repos":["iGame-Lab/LASOR"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/improving-robustness-and-accuracy-via","slug":"improving-robustness-and-accuracy-via","title":"Improving Robustness and Accuracy via Relative Information Encoding in 3D Human Pose Estimation","date":"2021-07-29","arxiv_id":"2107.13994","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-monocular-3d-human-pose","slug":"probabilistic-monocular-3d-human-pose","title":"Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows","date":"2021-07-29","arxiv_id":"2107.13788","repositories_listed":1,"syntology":{"n":9,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":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) · 0 unverified","sample_list":"/paper/probabilistic-monocular-3d-human-pose#ran","syntology_url":"https://syntology.ai/paper/2107.13788","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.13788"}},"official":{"repos":["twehrbein/Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/conditional-directed-graph-convolution-for-3d","slug":"conditional-directed-graph-convolution-for-3d","title":"Conditional Directed Graph Convolution for 3D Human Pose Estimation","date":"2021-07-16","arxiv_id":"2107.07797","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/conditional-directed-graph-convolution-for-3d#ran","syntology_url":"https://syntology.ai/paper/2107.07797","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07797"}},"official":null}},{"url":"/paper/real-time-multi-view-3d-human-pose-estimation","slug":"real-time-multi-view-3d-human-pose-estimation","title":"Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge Sensors","date":"2021-06-28","arxiv_id":"2106.14729","repositories_listed":1,"syntology":null},{"url":"/paper/part-aware-measurement-for-robust-multi-view-1","slug":"part-aware-measurement-for-robust-multi-view-1","title":"Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking","date":"2021-06-22","arxiv_id":"2106.11589","repositories_listed":1,"syntology":null},{"url":"/paper/adapted-human-pose-monocular-3d-human-pose","slug":"adapted-human-pose-monocular-3d-human-pose","title":"Adapted Human Pose: Monocular 3D Human Pose Estimation with Zero Real 3D Pose Data","date":"2021-05-23","arxiv_id":"2105.10837","repositories_listed":1,"syntology":null},{"url":"/paper/3d-human-pose-regression-using-graph","slug":"3d-human-pose-regression-using-graph","title":"3D Human Pose Regression using Graph Convolutional Network","date":"2021-05-21","arxiv_id":"2105.10379","repositories_listed":1,"syntology":null},{"url":"/paper/body-meshes-as-points","slug":"body-meshes-as-points","title":"Body Meshes as Points","date":"2021-05-06","arxiv_id":"2105.02467","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/body-meshes-as-points#ran","syntology_url":"https://syntology.ai/paper/2105.02467","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.02467"}},"official":{"repos":["jfzhang95/BMP"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/poseaug-a-differentiable-pose-augmentation","slug":"poseaug-a-differentiable-pose-augmentation","title":"PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation","date":"2021-05-06","arxiv_id":"2105.02465","repositories_listed":1,"syntology":null},{"url":"/paper/flex-parameter-free-multi-view-3d-human","slug":"flex-parameter-free-multi-view-3d-human","title":"FLEX: Extrinsic Parameters-free Multi-view 3D Human Motion Reconstruction","date":"2021-05-05","arxiv_id":"2105.01937","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/flex-parameter-free-multi-view-3d-human#ran","syntology_url":"https://syntology.ai/paper/2105.01937","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.01937"}},"official":{"repos":["BrianG13/FLEX"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/agora-avatars-in-geography-optimized-for","slug":"agora-avatars-in-geography-optimized-for","title":"AGORA: Avatars in Geography Optimized for Regression Analysis","date":"2021-04-29","arxiv_id":"2104.14643","repositories_listed":1,"syntology":null},{"url":"/paper/estimating-egocentric-3d-human-pose-in-global","slug":"estimating-egocentric-3d-human-pose-in-global","title":"Estimating Egocentric 3D Human Pose in Global Space","date":"2021-04-27","arxiv_id":"2104.13454","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":3,"n_ran_checked":3,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":6,"phrase":"5 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/estimating-egocentric-3d-human-pose-in-global#ran","syntology_url":"https://syntology.ai/paper/2104.13454","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.13454"}},"official":{"repos":["jianwang-mpi/GlobalEgoMocap"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lifting-monocular-events-to-3d-human-poses","slug":"lifting-monocular-events-to-3d-human-poses","title":"Lifting Monocular Events to 3D Human Poses","date":"2021-04-21","arxiv_id":"2104.10609","repositories_listed":1,"syntology":null},{"url":"/paper/pare-part-attention-regressor-for-3d-human","slug":"pare-part-attention-regressor-for-3d-human","title":"PARE: Part Attention Regressor for 3D Human Body Estimation","date":"2021-04-17","arxiv_id":"2104.08527","repositories_listed":1,"syntology":null},{"url":"/paper/3dcrowdnet-2d-human-pose-guided3d-crowd-human","slug":"3dcrowdnet-2d-human-pose-guided3d-crowd-human","title":"Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes","date":"2021-04-15","arxiv_id":"2104.07300","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/3dcrowdnet-2d-human-pose-guided3d-crowd-human#ran","syntology_url":"https://syntology.ai/paper/2104.07300","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.07300"}},"official":{"repos":["hongsukchoi/3dcrowdnet_release"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/on-self-contact-and-human-pose","slug":"on-self-contact-and-human-pose","title":"On Self-Contact and Human Pose","date":"2021-04-07","arxiv_id":"2104.03176","repositories_listed":1,"syntology":null},{"url":"/paper/human-poseitioning-system-hps-3d-human-pose","slug":"human-poseitioning-system-hps-3d-human-pose","title":"Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensors","date":"2021-03-31","arxiv_id":"2103.17265","repositories_listed":1,"syntology":null},{"url":"/paper/bilevel-online-adaptation-for-out-of-domain","slug":"bilevel-online-adaptation-for-out-of-domain","title":"Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction","date":"2021-03-30","arxiv_id":"2103.16449","repositories_listed":1,"syntology":null},{"url":"/paper/graph-stacked-hourglass-networks-for-3d-human","slug":"graph-stacked-hourglass-networks-for-3d-human","title":"Graph Stacked Hourglass Networks for 3D Human Pose Estimation","date":"2021-03-30","arxiv_id":"2103.16385","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":10,"n_ran_checked":11,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":10,"n_pointer_only":15,"phrase":"12 ran (of which 10 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 1 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/graph-stacked-hourglass-networks-for-3d-human#ran","syntology_url":"https://syntology.ai/paper/2103.16385","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.16385"}},"official":null}},{"url":"/paper/context-modeling-in-3d-human-pose-estimation","slug":"context-modeling-in-3d-human-pose-estimation","title":"Context Modeling in 3D Human Pose Estimation: A Unified Perspective","date":"2021-03-29","arxiv_id":"2103.15507","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":1,"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/context-modeling-in-3d-human-pose-estimation#ran","syntology_url":"https://syntology.ai/paper/2103.15507","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.15507"}},"official":null}},{"url":"/paper/lifting-transformer-for-3d-human-pose","slug":"lifting-transformer-for-3d-human-pose","title":"Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation","date":"2021-03-26","arxiv_id":"2103.14304","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"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, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/lifting-transformer-for-3d-human-pose#ran","syntology_url":"https://syntology.ai/paper/2103.14304","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.14304"}},"official":{"repos":["Vegetebird/StridedTransformer-Pose3D"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/em-pose-3d-human-pose-estimation-from-sparse","slug":"em-pose-3d-human-pose-estimation-from-sparse","title":"EM-POSE: 3D Human Pose Estimation From Sparse Electromagnetic Trackers","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/modulated-graph-convolutional-network-for-3d","slug":"modulated-graph-convolutional-network-for-3d","title":"Modulated Graph Convolutional Network for 3D Human Pose Estimation","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/deep-learning-based-human-pose-estimation-a","slug":"deep-learning-based-human-pose-estimation-a","title":"Deep Learning-Based Human Pose Estimation: A Survey","date":"2020-12-24","arxiv_id":"2012.13392","repositories_listed":1,"syntology":null},{"url":"/paper/graph-and-temporal-convolutional-networks-for","slug":"graph-and-temporal-convolutional-networks-for","title":"Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos","date":"2020-12-22","arxiv_id":"2012.11806","repositories_listed":1,"syntology":null},{"url":"/paper/end-to-end-human-pose-and-mesh-reconstruction","slug":"end-to-end-human-pose-and-mesh-reconstruction","title":"End-to-End Human Pose and Mesh Reconstruction with Transformers","date":"2020-12-17","arxiv_id":"2012.09760","repositories_listed":1,"syntology":null},{"url":"/paper/invariant-teacher-and-equivariant-student-for","slug":"invariant-teacher-and-equivariant-student-for","title":"Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation","date":"2020-12-17","arxiv_id":"2012.09398","repositories_listed":1,"syntology":null},{"url":"/paper/canonpose-self-supervised-monocular-3d-human","slug":"canonpose-self-supervised-monocular-3d-human","title":"CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild","date":"2020-11-30","arxiv_id":"2011.14679","repositories_listed":1,"syntology":null},{"url":"/paper/pose2pose-3d-positional-pose-guided-3d","slug":"pose2pose-3d-positional-pose-guided-3d","title":"Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimation","date":"2020-11-23","arxiv_id":"2011.11534","repositories_listed":1,"syntology":null},{"url":"/paper/beyond-static-features-for-temporally","slug":"beyond-static-features-for-temporally","title":"Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video","date":"2020-11-17","arxiv_id":"2011.08627","repositories_listed":1,"syntology":null},{"url":"/paper/residual-pose-a-decoupled-approach-for-depth","slug":"residual-pose-a-decoupled-approach-for-depth","title":"Residual Pose: A Decoupled Approach for Depth-based 3D Human Pose Estimation","date":"2020-11-10","arxiv_id":"2011.05010","repositories_listed":1,"syntology":null},{"url":"/paper/temporal-smoothing-for-3d-human-pose","slug":"temporal-smoothing-for-3d-human-pose","title":"Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded People","date":"2020-10-31","arxiv_id":"2011.00250","repositories_listed":1,"syntology":null},{"url":"/paper/hperl-3d-human-pose-estimation-from-rgb-and","slug":"hperl-3d-human-pose-estimation-from-rgb-and","title":"HPERL: 3D Human Pose Estimation from RGB and LiDAR","date":"2020-10-16","arxiv_id":"2010.08221","repositories_listed":1,"syntology":null},{"url":"/paper/synthetic-training-for-accurate-3d-human-pose","slug":"synthetic-training-for-accurate-3d-human-pose","title":"Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild","date":"2020-09-21","arxiv_id":"2009.10013","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"8 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/synthetic-training-for-accurate-3d-human-pose#ran","syntology_url":"https://syntology.ai/paper/2009.10013","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.10013"}},"official":{"repos":["akashsengupta1997/STRAPS-3DHumanShapePose"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/smap-single-shot-multi-person-absolute-3d","slug":"smap-single-shot-multi-person-absolute-3d","title":"SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation","date":"2020-08-26","arxiv_id":"2008.11469","repositories_listed":1,"syntology":null},{"url":"/paper/monocular-expressive-body-regression-through","slug":"monocular-expressive-body-regression-through","title":"Monocular Expressive Body Regression through Body-Driven Attention","date":"2020-08-20","arxiv_id":"2008.09062","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/monocular-expressive-body-regression-through#ran","syntology_url":"https://syntology.ai/paper/2008.09062","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.09062"}},"official":{"repos":["vchoutas/expose"],"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/weakly-supervised-generative-network-for","slug":"weakly-supervised-generative-network-for","title":"Weakly Supervised Generative Network for Multiple 3D Human Pose Hypotheses","date":"2020-08-13","arxiv_id":"2008.05770","repositories_listed":1,"syntology":{"n":11,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":9,"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) · 9 unverified","sample_list":"/paper/weakly-supervised-generative-network-for#ran","syntology_url":"https://syntology.ai/paper/2008.05770","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.05770"}},"official":{"repos":["chaneyddtt/weakly-supervised-3d-pose-generator"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/i2l-meshnet-image-to-lixel-prediction-network-1","slug":"i2l-meshnet-image-to-lixel-prediction-network-1","title":"I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image","date":"2020-08-09","arxiv_id":"2008.03713","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":3,"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) · 0 unverified","sample_list":"/paper/i2l-meshnet-image-to-lixel-prediction-network-1#ran","syntology_url":"https://syntology.ai/paper/2008.03713","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.03713"}},"official":{"repos":["mks0601/I2L-MeshNet_RELEASE"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-cross-modal-alignment-for-multi","slug":"unsupervised-cross-modal-alignment-for-multi","title":"Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation","date":"2020-08-04","arxiv_id":"2008.01388","repositories_listed":1,"syntology":null},{"url":"/paper/a-comprehensive-study-of-weight-sharing-in","slug":"a-comprehensive-study-of-weight-sharing-in","title":"A Comprehensive Study of Weight Sharing in Graph Networks for 3D Human Pose Estimation","date":"2020-08-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/combining-implicit-function-learning-and","slug":"combining-implicit-function-learning-and","title":"Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction","date":"2020-07-22","arxiv_id":"2007.11432","repositories_listed":1,"syntology":null},{"url":"/paper/sizer-a-dataset-and-model-for-parsing-3d","slug":"sizer-a-dataset-and-model-for-parsing-3d","title":"SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing","date":"2020-07-22","arxiv_id":"2007.11610","repositories_listed":1,"syntology":null},{"url":"/paper/multi-person-3d-pose-estimation-in-crowded","slug":"multi-person-3d-pose-estimation-in-crowded","title":"Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View Geometry","date":"2020-07-21","arxiv_id":"2007.10986","repositories_listed":1,"syntology":{"n":19,"n_ran":14,"n_constructed":0,"n_ran_checked":14,"n_instrument":0,"n_unverified":5,"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) · 5 unverified","sample_list":"/paper/multi-person-3d-pose-estimation-in-crowded#ran","syntology_url":"https://syntology.ai/paper/2007.10986","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.10986"}},"official":{"repos":["HeCraneChen/3D-Crowd-Pose-Estimation-Based-on-MVG"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":14,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/srnet-improving-generalization-in-3d-human","slug":"srnet-improving-generalization-in-3d-human","title":"SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approach","date":"2020-07-18","arxiv_id":"2007.09389","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":3,"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) · 3 unverified","sample_list":"/paper/srnet-improving-generalization-in-3d-human#ran","syntology_url":"https://syntology.ai/paper/2007.09389","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.09389"}},"official":{"repos":["ailingzengzzz/Split-and-Recombine-Net"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/self-supervision-on-unlabelled-or-data-for","slug":"self-supervision-on-unlabelled-or-data-for","title":"Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation","date":"2020-07-16","arxiv_id":"2007.08354","repositories_listed":1,"syntology":null},{"url":"/paper/metrabs-metric-scale-truncation-robust","slug":"metrabs-metric-scale-truncation-robust","title":"MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation","date":"2020-07-12","arxiv_id":"2007.07227","repositories_listed":1,"syntology":null},{"url":"/paper/making-densepose-fast-and-light","slug":"making-densepose-fast-and-light","title":"Making DensePose fast and light","date":"2020-06-26","arxiv_id":"2006.15190","repositories_listed":1,"syntology":null},{"url":"/paper/cascaded-deep-monocular-3d-human-pose-1","slug":"cascaded-deep-monocular-3d-human-pose-1","title":"Cascaded deep monocular 3D human pose estimation with evolutionary training data","date":"2020-06-14","arxiv_id":"2006.07778","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/cascaded-deep-monocular-3d-human-pose-1#ran","syntology_url":"https://syntology.ai/paper/2006.07778","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.07778"}},"official":{"repos":["Nicholasli1995/EvoSkeleton"],"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/attention-mechanism-exploits-temporal","slug":"attention-mechanism-exploits-temporal","title":"Attention Mechanism Exploits Temporal Contexts: Real-Time 3D Human Pose Reconstruction","date":"2020-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/epipolar-transformers","slug":"epipolar-transformers","title":"Epipolar Transformers","date":"2020-05-10","arxiv_id":"2005.04551","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":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) · 1 unverified","sample_list":"/paper/epipolar-transformers#ran","syntology_url":"https://syntology.ai/paper/2005.04551","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.04551"}},"official":{"repos":["yihui-he/epipolar-transformers"],"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/motion-guided-3d-pose-estimation-from-videos","slug":"motion-guided-3d-pose-estimation-from-videos","title":"Motion Guided 3D Pose Estimation from Videos","date":"2020-04-29","arxiv_id":"2004.13985","repositories_listed":1,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/motion-guided-3d-pose-estimation-from-videos#ran","syntology_url":"https://syntology.ai/paper/2004.13985","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.13985"}},"official":null}},{"url":"/paper/multi-person-absolute-3d-human-pose","slug":"multi-person-absolute-3d-human-pose","title":"Multi-Person Absolute 3D Human Pose Estimation with Weak Depth Supervision","date":"2020-04-08","arxiv_id":"2004.03989","repositories_listed":1,"syntology":null},{"url":"/paper/exemplar-fine-tuning-for-3d-human-pose","slug":"exemplar-fine-tuning-for-3d-human-pose","title":"Exemplar Fine-Tuning for 3D Human Model Fitting Towards In-the-Wild 3D Human Pose Estimation","date":"2020-04-07","arxiv_id":"2004.03686","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/exemplar-fine-tuning-for-3d-human-pose#ran","syntology_url":"https://syntology.ai/paper/2004.03686","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.03686"}},"official":{"repos":["facebookresearch/eft"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/bodies-at-rest-3d-human-pose-and-shape","slug":"bodies-at-rest-3d-human-pose-and-shape","title":"Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data","date":"2020-04-02","arxiv_id":"2004.01166","repositories_listed":1,"syntology":null},{"url":"/paper/compressed-volumetric-heatmaps-for-multi","slug":"compressed-volumetric-heatmaps-for-multi","title":"Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation","date":"2020-04-01","arxiv_id":"2004.00329","repositories_listed":1,"syntology":null},{"url":"/paper/optical-non-line-of-sight-physics-based-3d","slug":"optical-non-line-of-sight-physics-based-3d","title":"Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation","date":"2020-03-31","arxiv_id":"2003.14414","repositories_listed":1,"syntology":null},{"url":"/paper/fusing-wearable-imus-with-multi-view-images","slug":"fusing-wearable-imus-with-multi-view-images","title":"Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach","date":"2020-03-25","arxiv_id":"2003.11163","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/fusing-wearable-imus-with-multi-view-images#ran","syntology_url":"https://syntology.ai/paper/2003.11163","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.11163"}},"official":{"repos":["CHUNYUWANG/imu-human-pose-pytorch"],"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/dynamic-multiscale-graph-neural-networks-for","slug":"dynamic-multiscale-graph-neural-networks-for","title":"Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction","date":"2020-03-17","arxiv_id":"2003.08802","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":3,"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/dynamic-multiscale-graph-neural-networks-for#ran","syntology_url":"https://syntology.ai/paper/2003.08802","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.08802"}},"official":null}},{"url":"/paper/gast-net-graph-attention-spatio-temporal","slug":"gast-net-graph-attention-spatio-temporal","title":"A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video","date":"2020-03-11","arxiv_id":"2003.14179","repositories_listed":1,"syntology":null},{"url":"/paper/hemlets-posh-learning-part-centric-heatmap","slug":"hemlets-posh-learning-part-centric-heatmap","title":"HEMlets PoSh: Learning Part-Centric Heatmap Triplets for 3D Human Pose and Shape Estimation","date":"2020-03-10","arxiv_id":"2003.04894","repositories_listed":1,"syntology":null}],"record_sha256":"a242bcbcf3bb2ebd57d0631cdfea7fdccbd708a66fb9b96cedee9c3df0e35bbd","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}