{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:TY4FXWG6BKUCFVAXHWYH7Z3NDB","short_pith_number":"pith:TY4FXWG6","schema_version":"1.0","canonical_sha256":"9e385bd8de0aa822d4173db07fe76d18796985265bc4d61ea4011b13e49c9dcc","source":{"kind":"arxiv","id":"2605.17354","version":1},"attestation_state":"computed","paper":{"title":"GeoHand: Unlocking Prior Geometry Knowledge for Monocular 3D Hand Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Liangchen Dai, Weiquan Lin, Xingyu Chen, Xu Tang, Yaoqing Hu","submitted_at":"2026-05-17T09:45:34Z","abstract_excerpt":"Monocular 3D hand reconstruction is intrinsically a geometric problem, yet RGB appearance features alone often struggle to resolve severe ambiguities caused by self-occlusions and hand-object interactions. While introducing depth can explicitly provide spatial cues, raw sensor-captured depth maps are extensively noisy and incomplete, limiting their usefulness for fine-grained hand reconstruction. To bridge this gap, we propose GeoHand, a novel framework that unlocks high-quality geometric priors from a frozen foundational monocular geometry estimator (MoGe2). Recognizing that these priors are "},"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":"2605.17354","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-17T09:45:34Z","cross_cats_sorted":[],"title_canon_sha256":"2782d6ac8b5705283ce1203d2dba9ed35606ac6d7b0d9862906e6ac49a1703e9","abstract_canon_sha256":"2131b5be7505052b7d668570f12ea95cb1172c56402b0b2355ab4b122ac998aa"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:53.860505Z","signature_b64":"ITVjvHABhxMTMc4yN6bq9Lv8pbjWU2MC7k96aKR0FT5HklSm0GxbDyxkXYBpeh9ZYR5GloMNmqGPEPbY0NYKBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9e385bd8de0aa822d4173db07fe76d18796985265bc4d61ea4011b13e49c9dcc","last_reissued_at":"2026-05-20T00:03:53.859724Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:53.859724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GeoHand: Unlocking Prior Geometry Knowledge for Monocular 3D Hand Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Liangchen Dai, Weiquan Lin, Xingyu Chen, Xu Tang, Yaoqing Hu","submitted_at":"2026-05-17T09:45:34Z","abstract_excerpt":"Monocular 3D hand reconstruction is intrinsically a geometric problem, yet RGB appearance features alone often struggle to resolve severe ambiguities caused by self-occlusions and hand-object interactions. While introducing depth can explicitly provide spatial cues, raw sensor-captured depth maps are extensively noisy and incomplete, limiting their usefulness for fine-grained hand reconstruction. To bridge this gap, we propose GeoHand, a novel framework that unlocks high-quality geometric priors from a frozen foundational monocular geometry estimator (MoGe2). Recognizing that these priors are "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17354","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/2605.17354/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-19T21:41:57.791546Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.724342Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"7b5be2c3dd0b4866398f9fcc7c6b56d42184de9b33164f47017cd03364c618a8"},"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":"2605.17354","created_at":"2026-05-20T00:03:53.859853+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.17354v1","created_at":"2026-05-20T00:03:53.859853+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17354","created_at":"2026-05-20T00:03:53.859853+00:00"},{"alias_kind":"pith_short_12","alias_value":"TY4FXWG6BKUC","created_at":"2026-05-20T00:03:53.859853+00:00"},{"alias_kind":"pith_short_16","alias_value":"TY4FXWG6BKUCFVAX","created_at":"2026-05-20T00:03:53.859853+00:00"},{"alias_kind":"pith_short_8","alias_value":"TY4FXWG6","created_at":"2026-05-20T00:03:53.859853+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/TY4FXWG6BKUCFVAXHWYH7Z3NDB","json":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB.json","graph_json":"https://pith.science/api/pith-number/TY4FXWG6BKUCFVAXHWYH7Z3NDB/graph.json","events_json":"https://pith.science/api/pith-number/TY4FXWG6BKUCFVAXHWYH7Z3NDB/events.json","paper":"https://pith.science/paper/TY4FXWG6"},"agent_actions":{"view_html":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB","download_json":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB.json","view_paper":"https://pith.science/paper/TY4FXWG6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.17354&json=true","fetch_graph":"https://pith.science/api/pith-number/TY4FXWG6BKUCFVAXHWYH7Z3NDB/graph.json","fetch_events":"https://pith.science/api/pith-number/TY4FXWG6BKUCFVAXHWYH7Z3NDB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB/action/storage_attestation","attest_author":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB/action/author_attestation","sign_citation":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB/action/citation_signature","submit_replication":"https://pith.science/pith/TY4FXWG6BKUCFVAXHWYH7Z3NDB/action/replication_record"}},"created_at":"2026-05-20T00:03:53.859853+00:00","updated_at":"2026-05-20T00:03:53.859853+00:00"}