{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:R657O6ZKCC54QEOYZKVQFDVOQC","short_pith_number":"pith:R657O6ZK","schema_version":"1.0","canonical_sha256":"8fbbf77b2a10bbc811d8caab028eae80a11c5d3f67125eb69b7b4785d6789166","source":{"kind":"arxiv","id":"2605.14925","version":1},"attestation_state":"computed","paper":{"title":"Road Maps as Free Geometric Priors: Weather-Invariant Drone Geo-Localization with GeoFuse","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"(2) Hangzhou Dianzi University), Tingyu Wang (2), Yunsong Fang (1), Zhedong Zheng (1) ((1) University of Macau","submitted_at":"2026-05-14T15:01:22Z","abstract_excerpt":"Drone-view geo-localization aims to match a query drone image, often captured under adverse weather conditions (e.g., rain, snow, fog), against a gallery of geo-tagged satellite images. Weather-induced degradations in the drone view, such as noise, reduced visibility, and partial occlusions, severely exacerbate the intrinsic cross-view domain gap. While prior methods predominantly rely on weather-specific architectures or data augmentations, they have largely overlooked road map data, a readily available modality that provides strong, inherently weather-invariant geometric layout cues (e.g., r"},"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":"2605.14925","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-14T15:01:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"566b89b67c93091c01764ef4bb4a33d347bafcaed91773a02ae26f73ca23d167","abstract_canon_sha256":"eb1c6b2b1e8c92a1f5877ffd066dd508bb6e97dc58ff378206af8286fc71a78d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:38:55.624730Z","signature_b64":"kvDgYKd3l5Roze/Z1pxQW+PqXLbYlGKRONWdTAFX4t0KzkYR8M7SrSN2VGxYjuz0I3znpJ6BhHVqnGso6SPgCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8fbbf77b2a10bbc811d8caab028eae80a11c5d3f67125eb69b7b4785d6789166","last_reissued_at":"2026-05-17T23:38:55.624106Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:38:55.624106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Road Maps as Free Geometric Priors: Weather-Invariant Drone Geo-Localization with GeoFuse","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"(2) Hangzhou Dianzi University), Tingyu Wang (2), Yunsong Fang (1), Zhedong Zheng (1) ((1) University of Macau","submitted_at":"2026-05-14T15:01:22Z","abstract_excerpt":"Drone-view geo-localization aims to match a query drone image, often captured under adverse weather conditions (e.g., rain, snow, fog), against a gallery of geo-tagged satellite images. Weather-induced degradations in the drone view, such as noise, reduced visibility, and partial occlusions, severely exacerbate the intrinsic cross-view domain gap. While prior methods predominantly rely on weather-specific architectures or data augmentations, they have largely overlooked road map data, a readily available modality that provides strong, inherently weather-invariant geometric layout cues (e.g., r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14925","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":""},"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":"2605.14925","created_at":"2026-05-17T23:38:55.624213+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.14925v1","created_at":"2026-05-17T23:38:55.624213+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14925","created_at":"2026-05-17T23:38:55.624213+00:00"},{"alias_kind":"pith_short_12","alias_value":"R657O6ZKCC54","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_16","alias_value":"R657O6ZKCC54QEOY","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_8","alias_value":"R657O6ZK","created_at":"2026-05-18T12:33:37.589309+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/R657O6ZKCC54QEOYZKVQFDVOQC","json":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC.json","graph_json":"https://pith.science/api/pith-number/R657O6ZKCC54QEOYZKVQFDVOQC/graph.json","events_json":"https://pith.science/api/pith-number/R657O6ZKCC54QEOYZKVQFDVOQC/events.json","paper":"https://pith.science/paper/R657O6ZK"},"agent_actions":{"view_html":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC","download_json":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC.json","view_paper":"https://pith.science/paper/R657O6ZK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.14925&json=true","fetch_graph":"https://pith.science/api/pith-number/R657O6ZKCC54QEOYZKVQFDVOQC/graph.json","fetch_events":"https://pith.science/api/pith-number/R657O6ZKCC54QEOYZKVQFDVOQC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC/action/storage_attestation","attest_author":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC/action/author_attestation","sign_citation":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC/action/citation_signature","submit_replication":"https://pith.science/pith/R657O6ZKCC54QEOYZKVQFDVOQC/action/replication_record"}},"created_at":"2026-05-17T23:38:55.624213+00:00","updated_at":"2026-05-17T23:38:55.624213+00:00"}