{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:FMR7DH4KDXXIECIOUL4DLLWC3J","short_pith_number":"pith:FMR7DH4K","schema_version":"1.0","canonical_sha256":"2b23f19f8a1dee82090ea2f835aec2da7af17723620febb0100b47bafa76b5ab","source":{"kind":"arxiv","id":"1504.06378","version":2},"attestation_state":"computed","paper":{"title":"Depth-based hand pose estimation: methods, data, and challenges","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Deva Ramanan, Gregory Rogez, James Steven Supancic III, Jamie Shotton, Yi Yang","submitted_at":"2015-04-24T02:37:37Z","abstract_excerpt":"Hand pose estimation has matured rapidly in recent years. The introduction of commodity depth sensors and a multitude of practical applications have spurred new advances. We provide an extensive analysis of the state-of-the-art, focusing on hand pose estimation from a single depth frame. To do so, we have implemented a considerable number of systems, and will release all software and evaluation code. We summarize important conclusions here: (1) Pose estimation appears roughly solved for scenes with isolated hands. However, methods still struggle to analyze cluttered scenes where hands may be i"},"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":"1504.06378","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-04-24T02:37:37Z","cross_cats_sorted":[],"title_canon_sha256":"309f5985bcc8bc60cc0b21f2a6b5e8b6d6dad21a383b26429c054418cfed0d20","abstract_canon_sha256":"7a892521465e7265de2535e6e5bb8f6627f899aca9f7859f279ada2bb609eb0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:16:48.763622Z","signature_b64":"zvgaZYYTiwxfpzwE69CMnTu6pSe7GU+LIe27aPMv6EEUkLhyeNr8ooQMjfVoWCl4w5uWUuYXXj0dyP3o1XclBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2b23f19f8a1dee82090ea2f835aec2da7af17723620febb0100b47bafa76b5ab","last_reissued_at":"2026-05-18T02:16:48.762924Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:16:48.762924Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Depth-based hand pose estimation: methods, data, and challenges","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Deva Ramanan, Gregory Rogez, James Steven Supancic III, Jamie Shotton, Yi Yang","submitted_at":"2015-04-24T02:37:37Z","abstract_excerpt":"Hand pose estimation has matured rapidly in recent years. The introduction of commodity depth sensors and a multitude of practical applications have spurred new advances. We provide an extensive analysis of the state-of-the-art, focusing on hand pose estimation from a single depth frame. To do so, we have implemented a considerable number of systems, and will release all software and evaluation code. We summarize important conclusions here: (1) Pose estimation appears roughly solved for scenes with isolated hands. However, methods still struggle to analyze cluttered scenes where hands may be i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1504.06378","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":""},"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":"1504.06378","created_at":"2026-05-18T02:16:48.763036+00:00"},{"alias_kind":"arxiv_version","alias_value":"1504.06378v2","created_at":"2026-05-18T02:16:48.763036+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1504.06378","created_at":"2026-05-18T02:16:48.763036+00:00"},{"alias_kind":"pith_short_12","alias_value":"FMR7DH4KDXXI","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_16","alias_value":"FMR7DH4KDXXIECIO","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_8","alias_value":"FMR7DH4K","created_at":"2026-05-18T12:29:19.899920+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/FMR7DH4KDXXIECIOUL4DLLWC3J","json":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J.json","graph_json":"https://pith.science/api/pith-number/FMR7DH4KDXXIECIOUL4DLLWC3J/graph.json","events_json":"https://pith.science/api/pith-number/FMR7DH4KDXXIECIOUL4DLLWC3J/events.json","paper":"https://pith.science/paper/FMR7DH4K"},"agent_actions":{"view_html":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J","download_json":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J.json","view_paper":"https://pith.science/paper/FMR7DH4K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1504.06378&json=true","fetch_graph":"https://pith.science/api/pith-number/FMR7DH4KDXXIECIOUL4DLLWC3J/graph.json","fetch_events":"https://pith.science/api/pith-number/FMR7DH4KDXXIECIOUL4DLLWC3J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J/action/storage_attestation","attest_author":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J/action/author_attestation","sign_citation":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J/action/citation_signature","submit_replication":"https://pith.science/pith/FMR7DH4KDXXIECIOUL4DLLWC3J/action/replication_record"}},"created_at":"2026-05-18T02:16:48.763036+00:00","updated_at":"2026-05-18T02:16:48.763036+00:00"}