{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:PIQ5QPQSXSGPZGS55R4ZNOZSBP","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":"2b83d0302c02d0484f0725e299ce59f0d06e94bf9501ec3106d267501d65d24c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-18T06:32:40Z","title_canon_sha256":"df645c16c6699a3382af5b2161d8579c87dce7b2753fae71efd380c9ac7ad075"},"schema_version":"1.0","source":{"id":"2311.10983","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.10983","created_at":"2026-07-05T07:14:25Z"},{"alias_kind":"arxiv_version","alias_value":"2311.10983v1","created_at":"2026-07-05T07:14:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.10983","created_at":"2026-07-05T07:14:25Z"},{"alias_kind":"pith_short_12","alias_value":"PIQ5QPQSXSGP","created_at":"2026-07-05T07:14:25Z"},{"alias_kind":"pith_short_16","alias_value":"PIQ5QPQSXSGPZGS5","created_at":"2026-07-05T07:14:25Z"},{"alias_kind":"pith_short_8","alias_value":"PIQ5QPQS","created_at":"2026-07-05T07:14:25Z"}],"graph_snapshots":[{"event_id":"sha256:6bc2419fe6d41e562a14761e8418fbeda7dcd4c4e47d18f50770dc5a044eb1fe","target":"graph","created_at":"2026-07-05T07:14:25Z","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/2311.10983/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we aim to improve the 3D reasoning ability of Transformers in multi-view 3D human pose estimation. Recent works have focused on end-to-end learning-based transformer designs, which struggle to resolve geometric information accurately, particularly during occlusion. Instead, we propose a novel hybrid model, MVGFormer, which has a series of geometric and appearance modules organized in an iterative manner. The geometry modules are learning-free and handle all viewpoint-dependent 3D tasks geometrically which notably improves the model's generalization ability. The appearance modules","authors_text":"Chunyu Wang, Han Hu, Jialiang Zhu, Steven L. Waslander, Ziwei Liao","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-18T06:32:40Z","title":"Multiple View Geometry Transformers for 3D Human Pose Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.10983","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":"sha256:2c6ab030b426cfbe4443894b0b3fd9581a49ae93db3c22f59268d14f118f3503","target":"record","created_at":"2026-07-05T07:14:25Z","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":"2b83d0302c02d0484f0725e299ce59f0d06e94bf9501ec3106d267501d65d24c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-18T06:32:40Z","title_canon_sha256":"df645c16c6699a3382af5b2161d8579c87dce7b2753fae71efd380c9ac7ad075"},"schema_version":"1.0","source":{"id":"2311.10983","kind":"arxiv","version":1}},"canonical_sha256":"7a21d83e12bc8cfc9a5dec7996bb320bd27f563893715a34b3c0690ee7307386","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a21d83e12bc8cfc9a5dec7996bb320bd27f563893715a34b3c0690ee7307386","first_computed_at":"2026-07-05T07:14:25.840723Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:14:25.840723Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H9EvQgi9yhmgGmt9xAmx3z3om27E05biB1RVAucoQfR3kRcvs56j4p0Ptbg/MxS5UdP2dJpaDQgeAF6hN/PhCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:14:25.841256Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.10983","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c6ab030b426cfbe4443894b0b3fd9581a49ae93db3c22f59268d14f118f3503","sha256:6bc2419fe6d41e562a14761e8418fbeda7dcd4c4e47d18f50770dc5a044eb1fe"],"state_sha256":"2ca50b0f0e123786f373ee719f3e4b70c739539ece23a5237298aa69122680c6"}