{"as_of":"2026-08-16T19:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b44b3d6deac0a7f3eac2a61e8e8c6f022ffbda1963c349a08b45e16d4b3fe5fb","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:27:40.449590Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.07172/citation-record","integrity":"/paper/1908.07172/integrity","json":"/paper/1908.07172/citation-record.json","paper":"/paper/1908.07172"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:41.040834Z","title":null,"venue":null,"work_id":"a5c905db-b0cc-4fea-a69c-8c6819e58556","year":null},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.280831Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:c56f749b3a81e7e5a42ca2e1f3abf598c8f5a00a3a8f86f292e705c879fdbc3f","observation_id":"0e3eb56c-1531-4658-9da5-5e139faf8312","resolution":{"observed_at":"2026-08-14T12:27:41.045198Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:41.023269Z","title":"2d human pose estimation: New benchmark and state of the art analysis","venue":null,"work_id":"be73b5dc-13bd-4b4b-8664-6a0d40c4a2bf","year":2014},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.286670Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:8a64a0bbae58c5233693172d9b361d761fae3785108bc1d68858eedd8e394a02","observation_id":"222d02b8-ad38-488a-89e3-c9a34a8b22fc","resolution":{"observed_at":"2026-08-14T12:27:41.028842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01271","last_updated":"2018-04-19T14:32:38Z","snapshot_observed_at":"2026-08-13T10:37:24.864456Z","submitted_at":"2018-03-04T00:20:29Z","title":"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01271","snapshot_observed_at":"2026-08-14T12:27:40.291091Z","title":"Zico Kolter, and Vladlen Koltun","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.291091Z"},"links":{"cited_paper":"/paper/1803.01271","citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:905544c850d98479bb7c1488c5e31a14290cb2ce9d266b89668df2a7559f2795","observation_id":"afa97c10-dfff-467c-bc3f-887dbd549fcc","resolution":{"observed_at":"2026-08-14T12:27:40.291091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:41.002252Z","title":"Keep it smpl: Automatic estimation of 3D human pose and shape from a single image","venue":null,"work_id":"306157fe-613f-4844-bbf4-ed413d000a2d","year":2016},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.295676Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:5c20c75023c8374bca1324e36de0a1cdb8a1c6e1c609a98b41d8c3bbdb90bba7","observation_id":"af260631-a729-44ee-9647-8df5653979a5","resolution":{"observed_at":"2026-08-14T12:27:41.007464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.981374Z","title":"Learning 3d hu- man pose from structure and motion","venue":null,"work_id":"a35817f3-b98e-4bc4-9a45-daa22ffcd97a","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.299658Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:6add4f754f93577a8b1e4d06ea2b45c404b0d563ba18a46df1b8982626b0f632","observation_id":"126d0cd4-dcbb-4af9-82ee-7b109aca5fbf","resolution":{"observed_at":"2026-08-14T12:27:40.985781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.963650Z","title":"Towards multi-pose guided virtual try-on network","venue":null,"work_id":"2d73becd-d95b-497b-985b-640f2d00f3ad","year":2019},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.304414Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:665aa804e888b45c7ac32798660cd8fae596815a61f81345131a0fc97f4799db","observation_id":"ecdbb7ca-eb2a-44ce-ab2e-26dfd4af718a","resolution":{"observed_at":"2026-08-14T12:27:40.968735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.948880Z","title":"Flow-navigated warping gan for video virtual try-on","venue":null,"work_id":"d51ca9a6-ac38-4f73-9f3b-473a0eeb1a5b","year":2019},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.308719Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:e99c5a072192ba4070bd0fe4a5f34f1d9cf20da9406dbbbc85fb456d989878ff","observation_id":"7dcc2ad4-8f8e-459c-9b69-3a57fe5a9ed8","resolution":{"observed_at":"2026-08-14T12:27:40.954739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.932335Z","title":"Self-supervised video representation learn- ing with odd-one-out networks","venue":null,"work_id":"a130b2f6-910c-482c-b04b-11f6b5cd5294","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.313641Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:84e05fd6aad87d17f778ac27e9ff2f8ef23c8c165c23c48b493fb7ca8c61793e","observation_id":"927c191a-0f2b-4922-906f-84ff9088a817","resolution":{"observed_at":"2026-08-14T12:27:40.936917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.914445Z","title":"Learning bi- linear models for two-factor problems in vision","venue":null,"work_id":"ecbccab5-d669-4503-ad59-3191c973bb77","year":1997},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.318167Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:dc1f82bf1d8a282bc21bc4cf343299833160c85a0a7c70bb1126a874b6762b4e","observation_id":"8d566b17-325f-4033-9d06-278f0494b9bc","resolution":{"observed_at":"2026-08-14T12:27:40.920175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.897208Z","title":"Devnet: A deep event network for mul- timedia event detection and evidence recounting","venue":null,"work_id":"8778d326-57aa-43b5-a61a-42fab4975700","year":2015},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.322170Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:feae5f3e27855c41aab9304b3df64c971f815cffac2e2765eee7e27771c91aec","observation_id":"44edebe6-5eae-478b-b119-dd76f5bb25fa","resolution":{"observed_at":"2026-08-14T12:27:40.902228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.883028Z","title":"Recognizing an action using its name: A knowledge-based approach","venue":null,"work_id":"69461627-ac24-4120-9f28-91e5556a60d0","year":2016},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.327013Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:a21b4df57cb0e348637a93e265f8e70aea7489431ea30a8456142e985c7afde1","observation_id":"78279242-4ebb-4073-9c09-30d1d51f5ec5","resolution":{"observed_at":"2026-08-14T12:27:40.888048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.869572Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"6a2d2691-b62c-45db-8931-4b7eb73ab8e8","year":2016},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.331349Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:b38ea0deecebd54d35566ff7d6cd2cf79441cfb39667a4e4b9f01be2b445ae3f","observation_id":"d2edaddd-0a52-48b6-ba70-db78dee3caf9","resolution":{"observed_at":"2026-08-14T12:27:40.874088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.853998Z","title":"Exploiting temporal information for 3d human pose estimation","venue":null,"work_id":"88887b62-c532-45b9-a8af-4dce65f442e8","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.335337Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:cad348dac025ca2bbcb5f4aea614ee50d07f18d82e142e935ba785704b5c3ac3","observation_id":"73745829-7ec8-44cb-877c-75260bfffd93","resolution":{"observed_at":"2026-08-14T12:27:40.859784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.840135Z","title":"Clustered pose and nonlinear appearance models for human pose estimation","venue":null,"work_id":"fee6674b-d892-499d-b454-0d4cccd6f99d","year":2010},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.339844Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:64b4858984faaede41afde26371caf79e3b5ad2577a8b67df8dc668c6662670b","observation_id":"fb38cb07-8e8d-4110-aa15-9308c056d491","resolution":{"observed_at":"2026-08-14T12:27:40.845113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.827823Z","title":"Black, David W","venue":null,"work_id":"020a225f-95d3-433e-a7d9-8a7295caba64","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.343947Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:62f55aed58a855a80dbd6089dca624eead64c5601a09cdba595925d9010809cb","observation_id":"a4fb329c-76ae-404b-acbd-f200f15a2d4b","resolution":{"observed_at":"2026-08-14T12:27:40.831515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.815348Z","title":"Learning 3d human dynamics from video.IEEE Con- ference on Computer Vision and Pattern Recognition, CVPR, 2019","venue":null,"work_id":"30835e6a-9152-4ae0-8ee1-5ab5db41faef","year":2019},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.348641Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:bb753ba29777b5e314e4ee382a2401d6b9c896d3114f886c38e4155804d5b9dd","observation_id":"9255e110-fa0e-4275-80e5-67e43b002564","resolution":{"observed_at":"2026-08-14T12:27:40.819541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.804309Z","title":"Unite the peo- ple: Closing the loop between 3d and 2d human representa- tions","venue":null,"work_id":"29a4ca20-cd54-4f07-a716-e3973443eab9","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.353123Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:b1a2572c03d284401b2a155f0be860fa10e0e047ee126c88089646eda6faad81","observation_id":"69b69567-3d35-4e9c-9b6a-d7c9cbec100f","resolution":{"observed_at":"2026-08-14T12:27:40.808231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.792827Z","title":"Unsupervised representation learning by sort- ing sequences","venue":null,"work_id":"aede4221-4551-4127-9593-49424313b2e7","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.357924Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:8f464a757a28ab21540ddad0cf3703b42377d418e6d42bf1456c9d954e2590e8","observation_id":"99696959-bf93-423e-8f1b-761f2c2bddaf","resolution":{"observed_at":"2026-08-14T12:27:40.796907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.780630Z","title":"T-c3d: Temporal convolutional 3d network for real- time action recognition","venue":null,"work_id":"db76db52-6302-44fa-9b5a-7a101b13b20a","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.362227Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:4dae855256e76c0cefddb1d8f1590079de39cb171658bba7fb9e9a296dce66a4","observation_id":"e56466d9-ce0b-4d64-b489-87b8de276e58","resolution":{"observed_at":"2026-08-14T12:27:40.785101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.767961Z","title":"Accurate estimation of human body orientation from rgb-d sensors","venue":null,"work_id":"06c3255f-e2b1-47f2-8519-73ef11544a06","year":2013},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.366393Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:03776fe7f4b927ce6dd453ef6a998321dce117157678670796a67908e7f203d0","observation_id":"dadcd37f-8afc-4be3-a796-d6d428e8c6a8","resolution":{"observed_at":"2026-08-14T12:27:40.772154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.757031Z","title":"Mosh: Motion and shape capture from sparse markers","venue":null,"work_id":"0cdbe20b-abd9-446d-9191-505c18786264","year":2014},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.370515Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:a348a2aca6735949b5b44521700bb83f37928480cfb94dccd9867584e7677d9d","observation_id":"cbf567b8-9093-4e1d-be5f-d46856a52f30","resolution":{"observed_at":"2026-08-14T12:27:40.760863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.745990Z","title":null,"venue":null,"work_id":"aff13a12-daf4-4c07-aea4-d92894a8eaef","year":2015},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.374869Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:6bdc5a3d2237c0f4bd7c034e5a445ed331a3dfc8750d7551d16919604250b4db","observation_id":"227e715a-d0e3-4b5d-b861-2bfbf4590002","resolution":{"observed_at":"2026-08-14T12:27:40.749730Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.734910Z","title":"A progressive search paradigm for the internet of things","venue":null,"work_id":"64d6ec95-c6e2-4f6a-bd7e-53a3576afe56","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.380222Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:7ce8e3fa36ec63fbc65db05b03cebb456db2acfb3c8c9b482724044600143430","observation_id":"19b9196d-f8f2-446a-aeaf-91f72b060576","resolution":{"observed_at":"2026-08-14T12:27:40.739041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.723121Z","title":null,"venue":null,"work_id":"69a522bf-ca80-465b-8c7e-294d78ba6792","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.384655Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:c961c330729db46fba414709750b140fbbbd3e3a682ae752a708d21f87908f3f","observation_id":"ead2fe08-2137-427b-9486-f9f6bc82c729","resolution":{"observed_at":"2026-08-14T12:27:40.727130Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.710922Z","title":"Shuf- fle and learn: unsupervised learning using temporal order verification","venue":null,"work_id":"32243865-a914-4a70-8f3c-85b8a0c1970e","year":2016},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.388981Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:ab6accbaa0897dc803a2983bc1e56b4545e4568417497e5f20f9fd0b3ec59d1a","observation_id":"3ce8de19-5ac5-40e4-8d93-85bc76237a06","resolution":{"observed_at":"2026-08-14T12:27:40.715421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.696962Z","title":"Neural body fitting: Unifying deep learning and model based human pose and shape es- timation","venue":null,"work_id":"a17f50a7-2a85-48a0-889c-4be6d377781f","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.392963Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:98621f7688133b82d5585420e1e25420036a1a91d2a41f22a9c2c7081fc75170","observation_id":"0b537451-0966-47d8-8b40-2c551639ed69","resolution":{"observed_at":"2026-08-14T12:27:40.701961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.684526Z","title":"Learning to estimate 3D human pose and shape from a single color image","venue":null,"work_id":"a1e0bf01-ff2d-4220-b102-b08bcdc0f52a","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.397441Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:4a13e8d19f66078380cec6642b9f5094a52ac54ae3c4e9ed833b1d6905dc4888","observation_id":"09dd4fb1-0640-41e3-8e39-ab0948b8ec98","resolution":{"observed_at":"2026-08-14T12:27:40.688538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.11742","last_updated":"2019-03-29T13:36:46Z","snapshot_observed_at":"2026-08-14T17:51:50.682168Z","submitted_at":"2018-11-28T18:56:36Z","title":"3D human pose estimation in video with temporal convolutions and semi-supervised training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.11742","snapshot_observed_at":"2026-08-14T12:27:40.401383Z","title":"3d human pose estimation in video with temporal convolutions and semi-supervised training","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.401383Z"},"links":{"cited_paper":"/paper/1811.11742","citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:0eee1adb439f33dc746a2b22a706e9c67f4d95bba33115547b5d3cddea2ed470","observation_id":"1228dcc4-ffa2-4b4b-b04a-45299b0f2de3","resolution":{"observed_at":"2026-08-14T12:27:40.401383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.669422Z","title":"Sfv: Reinforcement learning of physical skills from videos","venue":null,"work_id":"b595969c-0e54-4732-87fe-ff5792a3d0ab","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.405504Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:5da5c5194986bb19b15e32f3ea7b16c800c74774ca83f41da3824d79bf229fe9","observation_id":"161c7edc-24c7-4ad0-9743-4b9a6255393e","resolution":{"observed_at":"2026-08-14T12:27:40.675318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.653181Z","title":"Self- supervised learning of pose embeddings from spatiotempo- ral relations in videos","venue":null,"work_id":"7811e44e-e76a-44c0-9441-dc1ada5984db","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.409715Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:660fc9fe7d705d2f2856d26dc2bbdb6ba5d4ebcd8f000186da96cec3fcdd183c","observation_id":"e7fd8d8d-ab84-4725-b173-049a0c80854d","resolution":{"observed_at":"2026-08-14T12:27:40.658725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.634903Z","title":"Integral human pose regression","venue":null,"work_id":"747fcdff-189d-488b-90c5-73a409f71bdb","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.414228Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:465bf7b824c817dd49bac5df336af3040fe41afaf3151f95b92bf935ea9ead40","observation_id":"b865b4ae-8fe8-4085-a6f3-dfc84625f211","resolution":{"observed_at":"2026-08-14T12:27:40.640786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.616813Z","title":"Self-supervised learning of motion capture","venue":null,"work_id":"5fb5ebfe-b7c5-4a12-87e5-f99b08119214","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.418201Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:9bce7920eb262ece4b204d14f9c93500199307fc1925842b2311a54d6928fd63","observation_id":"27774a65-340d-478b-9f3b-c78ab9e9784b","resolution":{"observed_at":"2026-08-14T12:27:40.622850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.597474Z","title":"Attention is all you need","venue":null,"work_id":"794ecc0c-9c2f-4f2a-8bcb-60c42a6a40c7","year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.422772Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:13a437bd44998222e506aab565e05cb809691f2c60f4f69e8c6f72d1197b24cb","observation_id":"6c2b4c5d-dcd0-4fc2-aebd-59f3fbd93afe","resolution":{"observed_at":"2026-08-14T12:27:40.602089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.581856Z","title":"Recovering accurate 3d human pose in the wild using imus and a moving camera","venue":null,"work_id":"32a95dd7-ca70-4e8a-98b2-75a6960d1b37","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.427193Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:032e646f3e4e87bb00510c55c2bc4c00d00186703e1232e31bbe81d3db033866","observation_id":"ebc183e1-cde3-4b35-ae62-5cd3d5eaa014","resolution":{"observed_at":"2026-08-14T12:27:40.588061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.06475","last_updated":"2017-11-17T09:58:20Z","snapshot_observed_at":"2026-08-15T23:49:50.399859Z","submitted_at":"2017-11-17T09:58:20Z","title":"AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.06475","snapshot_observed_at":"2026-08-14T12:27:40.431632Z","title":"Ai challenger: A large-scale dataset for going deeper in image understanding","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.431632Z"},"links":{"cited_paper":"/paper/1711.06475","citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:b4d7cf943cca59e81915d66f603d7b75f6a2abb6d2c045aa10983f9002c063ae","observation_id":"b43fd8d4-ebcc-4ecd-8326-9edaed666a4b","resolution":{"observed_at":"2026-08-14T12:27:40.431632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.568087Z","title":"Monoperfcap: Human performance capture from monocular video","venue":null,"work_id":"a80d566a-fde4-4792-80f0-477e5bd22b2e","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.436307Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:985ce85a26e141739296c1cad2df1db581ba98e211850664b64237ec93e546c9","observation_id":"6ced6a17-dc0f-4a7b-b665-2d1992912719","resolution":{"observed_at":"2026-08-14T12:27:40.572637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.11328","last_updated":"2018-12-29T10:22:14Z","snapshot_observed_at":"2026-08-14T17:37:15.169396Z","submitted_at":"2018-12-29T10:22:14Z","title":"Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image","version":1},"cited_work":{"arxiv_id":"1812.11328","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.11328","snapshot_observed_at":"2026-08-14T12:27:40.485403Z","title":"Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image","venue":"cs.CV","work_id":"9f4ff0ab-89b6-4ddb-bd62-d504978ccd5e","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.440454Z"},"links":{"cited_paper":"/paper/1812.11328","citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:234741eb9df81b0dabb65c4d5f5bb7472b435163336e2f168e50b7823441ef34","observation_id":"4d92fc1a-5c46-49c7-bc57-6f2579b839a7","resolution":{"observed_at":"2026-08-14T12:27:40.492475Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.554992Z","title":"From actemes to action: A strongly-supervised representa- tion for detailed action understanding","venue":null,"work_id":"beb12cd7-1f6e-41a4-8e3a-1ff04fb5cfc2","year":2013},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.444971Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:610cf8ae025874e3076f331defc6d074cdfd0058c91f82f2865d4738127b3a28","observation_id":"0bbea367-e53a-42cb-bf2e-d668b4d0519a","resolution":{"observed_at":"2026-08-14T12:27:40.559455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:27:40.540993Z","title":"Monocap: Monocular human motion capture using a cnn coupled with a geometric prior","venue":null,"work_id":"779c6d9e-96aa-481c-ad18-ea6439007212","year":2018},"citing_paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:27:40.449590Z"},"links":{"citing_paper":"/paper/1908.07172"},"observation_digest":"sha256:fd965f4157235cebac8f0d96281e20a83edd87f007632dafade7ca82385ee30f","observation_id":"e724fd32-5cc4-4772-8cc4-558a74ac0e7b","resolution":{"observed_at":"2026-08-14T12:27:40.545938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.07172","last_updated":"2019-09-17T10:35:56Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T21:51:57.246174Z","submitted_at":"2019-08-20T05:35:58Z","title":"Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":32},"total_outbound_references":39},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:1908.07172."}