{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:I5PASVAPLWFNX75PKOWOZR2OBX","short_pith_number":"pith:I5PASVAP","schema_version":"1.0","canonical_sha256":"475e09540f5d8adbffaf53acecc74e0dc0ab08b55030949e2fe138753abd0bd8","source":{"kind":"arxiv","id":"2607.20116","version":1},"attestation_state":"computed","paper":{"title":"RIM: A Retrieval-In-Matching Framework for Cross-Domain Global Visual Localization of UAVs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingliang Hu, Geng Zhang, Shang Wang, Siyuan Duan, Xin Li, Zhimin Mao","submitted_at":"2026-07-22T13:20:26Z","abstract_excerpt":"Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisition-time and imaging-platform differences between UAV and reference imagery induce substantial cross-domain appearance and viewpoint shifts, challenging robust six-degree-of-freedom (6-DoF) pose estimation. We address these shifts by sampling UAV-viewpoint reference views from Google 3D Tiles across locations, altitudes, and orientations. A two-stage cross-domain fine-tuning recipe adapts SALAD using pose-near positives and geographically distan"},"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":"2607.20116","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-22T13:20:26Z","cross_cats_sorted":[],"title_canon_sha256":"e70f6aae7295f8ca9a2059f5e835a5fafca17edc5534856e013292f2a571685a","abstract_canon_sha256":"4cff7a0b314f5eb79fe87ea10acc56f0eb81f1e7b2fc09f51c3bf3e711d774e0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-23T01:25:02.180675Z","signature_b64":"nymRV/p7Qnh7VfcS+kF5BlZEB0wq91Cr4qgLgOoxlS2qa4bwHEI22gXWQ1upsw6W2wE+BtOj69IVOLWCAajUAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"475e09540f5d8adbffaf53acecc74e0dc0ab08b55030949e2fe138753abd0bd8","last_reissued_at":"2026-07-23T01:25:02.179890Z","signature_status":"signed_v1","first_computed_at":"2026-07-23T01:25:02.179890Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RIM: A Retrieval-In-Matching Framework for Cross-Domain Global Visual Localization of UAVs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingliang Hu, Geng Zhang, Shang Wang, Siyuan Duan, Xin Li, Zhimin Mao","submitted_at":"2026-07-22T13:20:26Z","abstract_excerpt":"Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisition-time and imaging-platform differences between UAV and reference imagery induce substantial cross-domain appearance and viewpoint shifts, challenging robust six-degree-of-freedom (6-DoF) pose estimation. We address these shifts by sampling UAV-viewpoint reference views from Google 3D Tiles across locations, altitudes, and orientations. A two-stage cross-domain fine-tuning recipe adapts SALAD using pose-near positives and geographically distan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20116","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/2607.20116/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":"2607.20116","created_at":"2026-07-23T01:25:02.180289+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.20116v1","created_at":"2026-07-23T01:25:02.180289+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20116","created_at":"2026-07-23T01:25:02.180289+00:00"},{"alias_kind":"pith_short_12","alias_value":"I5PASVAPLWFN","created_at":"2026-07-23T01:25:02.180289+00:00"},{"alias_kind":"pith_short_16","alias_value":"I5PASVAPLWFNX75P","created_at":"2026-07-23T01:25:02.180289+00:00"},{"alias_kind":"pith_short_8","alias_value":"I5PASVAP","created_at":"2026-07-23T01:25:02.180289+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/I5PASVAPLWFNX75PKOWOZR2OBX","json":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX.json","graph_json":"https://pith.science/api/pith-number/I5PASVAPLWFNX75PKOWOZR2OBX/graph.json","events_json":"https://pith.science/api/pith-number/I5PASVAPLWFNX75PKOWOZR2OBX/events.json","paper":"https://pith.science/paper/I5PASVAP"},"agent_actions":{"view_html":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX","download_json":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX.json","view_paper":"https://pith.science/paper/I5PASVAP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.20116&json=true","fetch_graph":"https://pith.science/api/pith-number/I5PASVAPLWFNX75PKOWOZR2OBX/graph.json","fetch_events":"https://pith.science/api/pith-number/I5PASVAPLWFNX75PKOWOZR2OBX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX/action/storage_attestation","attest_author":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX/action/author_attestation","sign_citation":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX/action/citation_signature","submit_replication":"https://pith.science/pith/I5PASVAPLWFNX75PKOWOZR2OBX/action/replication_record"}},"created_at":"2026-07-23T01:25:02.180289+00:00","updated_at":"2026-07-23T01:25:02.180289+00:00"}