{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:L5RLCGTPWNIEXIHOSTTQUEXKOU","short_pith_number":"pith:L5RLCGTP","schema_version":"1.0","canonical_sha256":"5f62b11a6fb3504ba0ee94e70a12ea752b7283ebe4e6d928bdb75503bc894b54","source":{"kind":"arxiv","id":"2203.16202","version":1},"attestation_state":"computed","paper":{"title":"Spatial-Temporal Parallel Transformer for Arm-Hand Dynamic Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiaxian Wu, Shuying Liu, Wenbin Wu, Yue Lin","submitted_at":"2022-03-30T10:51:41Z","abstract_excerpt":"We propose an approach to estimate arm and hand dynamics from monocular video by utilizing the relationship between arm and hand. Although monocular full human motion capture technologies have made great progress in recent years, recovering accurate and plausible arm twists and hand gestures from in-the-wild videos still remains a challenge. To solve this problem, our solution is proposed based on the fact that arm poses and hand gestures are highly correlated in most real situations. To fully exploit arm-hand correlation as well as inter-frame information, we carefully design a Spatial-Tempor"},"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":"2203.16202","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-30T10:51:41Z","cross_cats_sorted":[],"title_canon_sha256":"569e9c5ab82fa77ff5d015699ca9368a7c0cdf1c9f8881573ec9335015aac2e6","abstract_canon_sha256":"370e1f4b662fb4880b02b3daff3d325c675863e1ac0b06c12db3e55278d69987"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:10:08.563748Z","signature_b64":"Psz+3CN+jjOmZSWt+GLtDpc0ej2Yv8kXSD2ARzTaV5FA/gdi5o+5OBy7N2FYbCy/CvJEl8dNZMEU4lZpnPy4CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f62b11a6fb3504ba0ee94e70a12ea752b7283ebe4e6d928bdb75503bc894b54","last_reissued_at":"2026-07-05T04:10:08.563353Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:10:08.563353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Spatial-Temporal Parallel Transformer for Arm-Hand Dynamic Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiaxian Wu, Shuying Liu, Wenbin Wu, Yue Lin","submitted_at":"2022-03-30T10:51:41Z","abstract_excerpt":"We propose an approach to estimate arm and hand dynamics from monocular video by utilizing the relationship between arm and hand. Although monocular full human motion capture technologies have made great progress in recent years, recovering accurate and plausible arm twists and hand gestures from in-the-wild videos still remains a challenge. To solve this problem, our solution is proposed based on the fact that arm poses and hand gestures are highly correlated in most real situations. To fully exploit arm-hand correlation as well as inter-frame information, we carefully design a Spatial-Tempor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16202","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/2203.16202/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":"2203.16202","created_at":"2026-07-05T04:10:08.563408+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.16202v1","created_at":"2026-07-05T04:10:08.563408+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16202","created_at":"2026-07-05T04:10:08.563408+00:00"},{"alias_kind":"pith_short_12","alias_value":"L5RLCGTPWNIE","created_at":"2026-07-05T04:10:08.563408+00:00"},{"alias_kind":"pith_short_16","alias_value":"L5RLCGTPWNIEXIHO","created_at":"2026-07-05T04:10:08.563408+00:00"},{"alias_kind":"pith_short_8","alias_value":"L5RLCGTP","created_at":"2026-07-05T04:10:08.563408+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/L5RLCGTPWNIEXIHOSTTQUEXKOU","json":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU.json","graph_json":"https://pith.science/api/pith-number/L5RLCGTPWNIEXIHOSTTQUEXKOU/graph.json","events_json":"https://pith.science/api/pith-number/L5RLCGTPWNIEXIHOSTTQUEXKOU/events.json","paper":"https://pith.science/paper/L5RLCGTP"},"agent_actions":{"view_html":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU","download_json":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU.json","view_paper":"https://pith.science/paper/L5RLCGTP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.16202&json=true","fetch_graph":"https://pith.science/api/pith-number/L5RLCGTPWNIEXIHOSTTQUEXKOU/graph.json","fetch_events":"https://pith.science/api/pith-number/L5RLCGTPWNIEXIHOSTTQUEXKOU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU/action/storage_attestation","attest_author":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU/action/author_attestation","sign_citation":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU/action/citation_signature","submit_replication":"https://pith.science/pith/L5RLCGTPWNIEXIHOSTTQUEXKOU/action/replication_record"}},"created_at":"2026-07-05T04:10:08.563408+00:00","updated_at":"2026-07-05T04:10:08.563408+00:00"}