{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:NFALDIWXFD7CTO56ZWD72QRWUR","short_pith_number":"pith:NFALDIWX","schema_version":"1.0","canonical_sha256":"6940b1a2d728fe29bbbecd87fd4236a44d1f61bbd286af43c6c89f441ab99dbb","source":{"kind":"arxiv","id":"2410.20731","version":2},"attestation_state":"computed","paper":{"title":"BLAPose: Enhancing 3D Human Pose Estimation with Bone Length Adjustment","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chih-Hsiang Hsu, Jyh-Shing Roger Jang","submitted_at":"2024-10-28T04:50:27Z","abstract_excerpt":"Current approaches in 3D human pose estimation primarily focus on regressing 3D joint locations, often neglecting critical physical constraints such as bone length consistency and body symmetry. This work introduces a recurrent neural network architecture designed to capture holistic information across entire video sequences, enabling accurate prediction of bone lengths. To enhance training effectiveness, we propose a novel augmentation strategy using synthetic bone lengths that adhere to physical constraints. Moreover, we present a bone length adjustment method that preserves bone orientation"},"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":"2410.20731","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-28T04:50:27Z","cross_cats_sorted":[],"title_canon_sha256":"0995a65e4b630539574d73bda46ed87377a45b37d7565c6b2678d29d98cd6849","abstract_canon_sha256":"2d3456547fc84eab8ac293165502159ffe9e08d5fcceea7e66bb7f2c1bdd2ddf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:27:25.872762Z","signature_b64":"xP9eF7cTkBGqI1QzkWUc9PHWnEuANGmzUo5E0uRXxrSqX9W7gmMDO+9B0vcCEhGxHFNHPsq5wqMkiATWudqmBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6940b1a2d728fe29bbbecd87fd4236a44d1f61bbd286af43c6c89f441ab99dbb","last_reissued_at":"2026-07-05T09:27:25.872353Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:27:25.872353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BLAPose: Enhancing 3D Human Pose Estimation with Bone Length Adjustment","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chih-Hsiang Hsu, Jyh-Shing Roger Jang","submitted_at":"2024-10-28T04:50:27Z","abstract_excerpt":"Current approaches in 3D human pose estimation primarily focus on regressing 3D joint locations, often neglecting critical physical constraints such as bone length consistency and body symmetry. This work introduces a recurrent neural network architecture designed to capture holistic information across entire video sequences, enabling accurate prediction of bone lengths. To enhance training effectiveness, we propose a novel augmentation strategy using synthetic bone lengths that adhere to physical constraints. Moreover, we present a bone length adjustment method that preserves bone orientation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.20731","kind":"arxiv","version":2},"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/2410.20731/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":"2410.20731","created_at":"2026-07-05T09:27:25.872408+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.20731v2","created_at":"2026-07-05T09:27:25.872408+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.20731","created_at":"2026-07-05T09:27:25.872408+00:00"},{"alias_kind":"pith_short_12","alias_value":"NFALDIWXFD7C","created_at":"2026-07-05T09:27:25.872408+00:00"},{"alias_kind":"pith_short_16","alias_value":"NFALDIWXFD7CTO56","created_at":"2026-07-05T09:27:25.872408+00:00"},{"alias_kind":"pith_short_8","alias_value":"NFALDIWX","created_at":"2026-07-05T09:27:25.872408+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.20763","citing_title":"KASportsFormer: Kinematic Anatomy Enhanced Transformer for 3D Human Pose Estimation on Short Sports Scene Video","ref_index":8,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR","json":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR.json","graph_json":"https://pith.science/api/pith-number/NFALDIWXFD7CTO56ZWD72QRWUR/graph.json","events_json":"https://pith.science/api/pith-number/NFALDIWXFD7CTO56ZWD72QRWUR/events.json","paper":"https://pith.science/paper/NFALDIWX"},"agent_actions":{"view_html":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR","download_json":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR.json","view_paper":"https://pith.science/paper/NFALDIWX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.20731&json=true","fetch_graph":"https://pith.science/api/pith-number/NFALDIWXFD7CTO56ZWD72QRWUR/graph.json","fetch_events":"https://pith.science/api/pith-number/NFALDIWXFD7CTO56ZWD72QRWUR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR/action/storage_attestation","attest_author":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR/action/author_attestation","sign_citation":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR/action/citation_signature","submit_replication":"https://pith.science/pith/NFALDIWXFD7CTO56ZWD72QRWUR/action/replication_record"}},"created_at":"2026-07-05T09:27:25.872408+00:00","updated_at":"2026-07-05T09:27:25.872408+00:00"}