{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:TUCH26AXF3FTDW7HXEXNIS7DZQ","short_pith_number":"pith:TUCH26AX","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"},"canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","source":{"kind":"arxiv","id":"2507.10437","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.10437","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"arxiv_version","alias_value":"2507.10437v1","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.10437","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_12","alias_value":"TUCH26AXF3FT","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_16","alias_value":"TUCH26AXF3FTDW7H","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_8","alias_value":"TUCH26AX","created_at":"2026-07-05T11:36:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:TUCH26AXF3FTDW7HXEXNIS7DZQ","target":"record","payload":{"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"},"canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","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"},"source_kind":"arxiv","source_id":"2507.10437","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:36:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o+bFjxyBwWM8PnaNv6pFsin7kI0jSzEFfIBeVlz3mo/mOWJFxGCia/DAhcdCsssEX55FdPjCznVS0FBSB5EHCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T17:49:26.805797Z"},"content_sha256":"8e361548fa614edcac9241a1b626cfb9b64b18eae946aed0a602c45dbeaf2491","schema_version":"1.0","event_id":"sha256:8e361548fa614edcac9241a1b626cfb9b64b18eae946aed0a602c45dbeaf2491"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:TUCH26AXF3FTDW7HXEXNIS7DZQ","target":"graph","payload":{"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:36:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pT+L3cXr6sL+K/Or4eMIac6cn88Leos6vt+k9zjbquUJfoyTqRbSQoJTlcHFPh9w3kbxObgOg/ZXUgQRr3QmDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T17:49:26.806165Z"},"content_sha256":"6baa780111e4d9bebdf0675fd5e5915102b24e45de6a8e26ea2113b91eff6783","schema_version":"1.0","event_id":"sha256:6baa780111e4d9bebdf0675fd5e5915102b24e45de6a8e26ea2113b91eff6783"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/bundle.json","state_url":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-17T17:49:26Z","links":{"resolver":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ","bundle":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/bundle.json","state":"https://pith.science/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TUCH26AXF3FTDW7HXEXNIS7DZQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TUCH26AXF3FTDW7HXEXNIS7DZQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a5a2060e1d150b78e0e495f91cb6d8162782533b57cf7159b31c38093207b3ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-14T16:24:31Z","title_canon_sha256":"69b6a71a53b06e0e57e63f37fd6c89240e3b21eec760ce41c7172ac82e073af6"},"schema_version":"1.0","source":{"id":"2507.10437","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.10437","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"arxiv_version","alias_value":"2507.10437v1","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.10437","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_12","alias_value":"TUCH26AXF3FT","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_16","alias_value":"TUCH26AXF3FTDW7H","created_at":"2026-07-05T11:36:51Z"},{"alias_kind":"pith_short_8","alias_value":"TUCH26AX","created_at":"2026-07-05T11:36:51Z"}],"graph_snapshots":[{"event_id":"sha256:6baa780111e4d9bebdf0675fd5e5915102b24e45de6a8e26ea2113b91eff6783","target":"graph","created_at":"2026-07-05T11:36:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.10437/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"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","authors_text":"Alan Yuille, Guofeng Zhang, Jiawei Peng, Jieneng Chen, Qihao Liu, Shanshan Zhong, Wufei Ma, Zehan Zheng, Zhongzhan Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-14T16:24:31Z","title":"4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.10437","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8e361548fa614edcac9241a1b626cfb9b64b18eae946aed0a602c45dbeaf2491","target":"record","created_at":"2026-07-05T11:36:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a5a2060e1d150b78e0e495f91cb6d8162782533b57cf7159b31c38093207b3ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-14T16:24:31Z","title_canon_sha256":"69b6a71a53b06e0e57e63f37fd6c89240e3b21eec760ce41c7172ac82e073af6"},"schema_version":"1.0","source":{"id":"2507.10437","kind":"arxiv","version":1}},"canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d047d78172ecb31dbe7b92ed44be3cc37d0fb432280eddb0574c823dd35c305","first_computed_at":"2026-07-05T11:36:51.240275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:36:51.240275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GGKxXHZyHbQq1ZYwfyh7FFa5lvkOZtQEmGvrl4w0BtcyZUU1vE93p5bmKbThakkA6XOoUp6gMDtMC1HazHCWBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:36:51.240830Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.10437","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e361548fa614edcac9241a1b626cfb9b64b18eae946aed0a602c45dbeaf2491","sha256:6baa780111e4d9bebdf0675fd5e5915102b24e45de6a8e26ea2113b91eff6783"],"state_sha256":"b772aac18ae4ebfdc2ba77e55bb834de49c3fbe36bd37a0df4ff3c5fa2a2b311"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x070uhvQUv173KQR4BsTsAk8P0jnU4wBpiU9Rb+E7+6XjK3i3VYnarWSTuehWZnpnxbvaFsTQc98NrrNz3BRAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T17:49:26.808662Z","bundle_sha256":"aedcf6c647bf44fe553b9595ef31eb8edf0922403993e2686f5a7f798e3e09f8"}}