{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:URPZUUMKLI67B5MESBJD5G2J2T","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":"4de0ec79d21a9316e5671dd7c111b3275877268347a37e47ac4d5351ce947a1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-28T08:42:48Z","title_canon_sha256":"020ebe0e2b59b5525fca437eb05e5de7cfdf22b3ee140ff6bd6e840373820123"},"schema_version":"1.0","source":{"id":"2412.20082","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.20082","created_at":"2026-07-05T10:45:15Z"},{"alias_kind":"arxiv_version","alias_value":"2412.20082v2","created_at":"2026-07-05T10:45:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20082","created_at":"2026-07-05T10:45:15Z"},{"alias_kind":"pith_short_12","alias_value":"URPZUUMKLI67","created_at":"2026-07-05T10:45:15Z"},{"alias_kind":"pith_short_16","alias_value":"URPZUUMKLI67B5ME","created_at":"2026-07-05T10:45:15Z"},{"alias_kind":"pith_short_8","alias_value":"URPZUUMK","created_at":"2026-07-05T10:45:15Z"}],"graph_snapshots":[{"event_id":"sha256:ee65eaf6f256d6d53276bbc4f4daa0ac80cc437de43b5f47967cac507179aa96","target":"graph","created_at":"2026-07-05T10:45:15Z","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/2412.20082/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep visual odometry has demonstrated great advancements by learning-to-optimize technology. This approach heavily relies on the visual matching across frames. However, ambiguous matching in challenging scenarios leads to significant errors in geometric modeling and bundle adjustment optimization, which undermines the accuracy and robustness of pose estimation. To address this challenge, this paper proposes MambaVO, which conducts robust initialization, Mamba-based sequential matching refinement, and smoothed training to enhance the matching quality and improve the pose estimation. Specificall","authors_text":"Deying Li, Jian Zhao, Shuo Wang, Wanting Li, Xudong Cai, Yongcai Wang, Zhaoxin Fan, Zhe Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-28T08:42:48Z","title":"MambaVO: Deep Visual Odometry Based on Sequential Matching Refinement and Training Smoothing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20082","kind":"arxiv","version":2},"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":"sha256:96cd587a08daa0b82b616d44a4144f9c8a0e1c788186fa00db6c19c0e461838c","target":"record","created_at":"2026-07-05T10:45:15Z","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":"4de0ec79d21a9316e5671dd7c111b3275877268347a37e47ac4d5351ce947a1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-28T08:42:48Z","title_canon_sha256":"020ebe0e2b59b5525fca437eb05e5de7cfdf22b3ee140ff6bd6e840373820123"},"schema_version":"1.0","source":{"id":"2412.20082","kind":"arxiv","version":2}},"canonical_sha256":"a45f9a518a5a3df0f58490523e9b49d4e9d97af4b4f34c863b5be4380062b20f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a45f9a518a5a3df0f58490523e9b49d4e9d97af4b4f34c863b5be4380062b20f","first_computed_at":"2026-07-05T10:45:15.789515Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:45:15.789515Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lZSeijmE4ZuW6VCWYKtStHb4TN5uPaFGHwcorjnPJzsnT8543hY5dNUYXWHH716iZ1zGcKKx8580hzabXglRBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:45:15.789930Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.20082","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:96cd587a08daa0b82b616d44a4144f9c8a0e1c788186fa00db6c19c0e461838c","sha256:ee65eaf6f256d6d53276bbc4f4daa0ac80cc437de43b5f47967cac507179aa96"],"state_sha256":"1e7c94f5deb3730954e4595effb1a2350d6fbc9846148839755509018e1aa05f"}