{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:TUCH26AXF3FTDW7HXEXNIS7DZQ","short_pith_number":"pith:TUCH26AX","schema_version":"1.0","canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","source":{"kind":"arxiv","id":"2507.10437","version":1},"attestation_state":"computed","paper":{"title":"4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alan Yuille, Guofeng Zhang, Jiawei Peng, Jieneng Chen, Qihao Liu, Shanshan Zhong, Wufei Ma, Zehan Zheng, Zhongzhan Huang","submitted_at":"2025-07-14T16:24:31Z","abstract_excerpt":"Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is labor-intensive, and keypoint detectors trained on limited animal data are often unreliable. To address this, we propose 4D-Animal, a novel framework that reconstructs animatable 3D animals from videos without requiring sparse keypoint annotations. Our approach introduces a dense feature network that maps 2D representations to SMAL parameters, enhancing both the efficiency and stability of the fitting process. Furthermo"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.10437","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-14T16:24:31Z","cross_cats_sorted":[],"title_canon_sha256":"69b6a71a53b06e0e57e63f37fd6c89240e3b21eec760ce41c7172ac82e073af6","abstract_canon_sha256":"a5a2060e1d150b78e0e495f91cb6d8162782533b57cf7159b31c38093207b3ee"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:36:51.240830Z","signature_b64":"GGKxXHZyHbQq1ZYwfyh7FFa5lvkOZtQEmGvrl4w0BtcyZUU1vE93p5bmKbThakkA6XOoUp6gMDtMC1HazHCWBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","last_reissued_at":"2026-07-05T11:36:51.240275Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:36:51.240275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alan Yuille, Guofeng Zhang, Jiawei Peng, Jieneng Chen, Qihao Liu, Shanshan Zhong, Wufei Ma, Zehan Zheng, Zhongzhan Huang","submitted_at":"2025-07-14T16:24:31Z","abstract_excerpt":"Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is labor-intensive, and keypoint detectors trained on limited animal data are often unreliable. To address this, we propose 4D-Animal, a novel framework that reconstructs animatable 3D animals from videos without requiring sparse keypoint annotations. Our approach introduces a dense feature network that maps 2D representations to SMAL parameters, enhancing both the efficiency and stability of the fitting process. Furthermo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.10437","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.10437/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.10437","created_at":"2026-07-05T11:36:51.240335+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.10437v1","created_at":"2026-07-05T11:36:51.240335+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.10437","created_at":"2026-07-05T11:36:51.240335+00:00"},{"alias_kind":"pith_short_12","alias_value":"TUCH26AXF3FT","created_at":"2026-07-05T11:36:51.240335+00:00"},{"alias_kind":"pith_short_16","alias_value":"TUCH26AXF3FTDW7H","created_at":"2026-07-05T11:36:51.240335+00:00"},{"alias_kind":"pith_short_8","alias_value":"TUCH26AX","created_at":"2026-07-05T11:36:51.240335+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ","json":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ.json","graph_json":"https://pith.science/api/pith-number/TUCH26AXF3FTDW7HXEXNIS7DZQ/graph.json","events_json":"https://pith.science/api/pith-number/TUCH26AXF3FTDW7HXEXNIS7DZQ/events.json","paper":"https://pith.science/paper/TUCH26AX"},"agent_actions":{"view_html":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ","download_json":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ.json","view_paper":"https://pith.science/paper/TUCH26AX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.10437&json=true","fetch_graph":"https://pith.science/api/pith-number/TUCH26AXF3FTDW7HXEXNIS7DZQ/graph.json","fetch_events":"https://pith.science/api/pith-number/TUCH26AXF3FTDW7HXEXNIS7DZQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/action/storage_attestation","attest_author":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/action/author_attestation","sign_citation":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/action/citation_signature","submit_replication":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/action/replication_record"}},"created_at":"2026-07-05T11:36:51.240335+00:00","updated_at":"2026-07-05T11:36:51.240335+00:00"}