{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:52ZJU3KST7V3BKJ5WCFKBB5JPQ","short_pith_number":"pith:52ZJU3KS","schema_version":"1.0","canonical_sha256":"eeb29a6d529febb0a93db08aa087a97c3b43d4b5e95055960d9ec85e3d72869e","source":{"kind":"arxiv","id":"2009.05695","version":1},"attestation_state":"computed","paper":{"title":"RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Han-Pang Chiu, Karan Sikka, Niluthpol Chowdhury Mithun, Rakesh Kumar, Supun Samarasekera","submitted_at":"2020-09-12T01:18:45Z","abstract_excerpt":"We study an important, yet largely unexplored problem of large-scale cross-modal visual localization by matching ground RGB images to a geo-referenced aerial LIDAR 3D point cloud (rendered as depth images). Prior works were demonstrated on small datasets and did not lend themselves to scaling up for large-scale applications. To enable large-scale evaluation, we introduce a new dataset containing over 550K pairs (covering 143 km^2 area) of RGB and aerial LIDAR depth images. We propose a novel joint embedding based method that effectively combines the appearance and semantic cues from both modal"},"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":"2009.05695","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-12T01:18:45Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"7d27ea2210387aebf39957af21c1e465948ad2af10a01ce0179aa652a604088b","abstract_canon_sha256":"a954a8a00cd3462e7b365bdacacc7e5c0d127f20912d47dd73e1fe59351b5100"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:35:00.278999Z","signature_b64":"c8Ih/8v5lWujOLSCk14kpWoUzAIJ5hvXUlipegHtyn1oqvtzIg8Y8yr/qdwIoFKRLKf6W0jdRIWArFakW/L5BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eeb29a6d529febb0a93db08aa087a97c3b43d4b5e95055960d9ec85e3d72869e","last_reissued_at":"2026-07-05T01:35:00.278659Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:35:00.278659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Han-Pang Chiu, Karan Sikka, Niluthpol Chowdhury Mithun, Rakesh Kumar, Supun Samarasekera","submitted_at":"2020-09-12T01:18:45Z","abstract_excerpt":"We study an important, yet largely unexplored problem of large-scale cross-modal visual localization by matching ground RGB images to a geo-referenced aerial LIDAR 3D point cloud (rendered as depth images). Prior works were demonstrated on small datasets and did not lend themselves to scaling up for large-scale applications. To enable large-scale evaluation, we introduce a new dataset containing over 550K pairs (covering 143 km^2 area) of RGB and aerial LIDAR depth images. We propose a novel joint embedding based method that effectively combines the appearance and semantic cues from both modal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.05695","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/2009.05695/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":"2009.05695","created_at":"2026-07-05T01:35:00.278716+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.05695v1","created_at":"2026-07-05T01:35:00.278716+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.05695","created_at":"2026-07-05T01:35:00.278716+00:00"},{"alias_kind":"pith_short_12","alias_value":"52ZJU3KST7V3","created_at":"2026-07-05T01:35:00.278716+00:00"},{"alias_kind":"pith_short_16","alias_value":"52ZJU3KST7V3BKJ5","created_at":"2026-07-05T01:35:00.278716+00:00"},{"alias_kind":"pith_short_8","alias_value":"52ZJU3KS","created_at":"2026-07-05T01:35:00.278716+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/52ZJU3KST7V3BKJ5WCFKBB5JPQ","json":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ.json","graph_json":"https://pith.science/api/pith-number/52ZJU3KST7V3BKJ5WCFKBB5JPQ/graph.json","events_json":"https://pith.science/api/pith-number/52ZJU3KST7V3BKJ5WCFKBB5JPQ/events.json","paper":"https://pith.science/paper/52ZJU3KS"},"agent_actions":{"view_html":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ","download_json":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ.json","view_paper":"https://pith.science/paper/52ZJU3KS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.05695&json=true","fetch_graph":"https://pith.science/api/pith-number/52ZJU3KST7V3BKJ5WCFKBB5JPQ/graph.json","fetch_events":"https://pith.science/api/pith-number/52ZJU3KST7V3BKJ5WCFKBB5JPQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ/action/storage_attestation","attest_author":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ/action/author_attestation","sign_citation":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ/action/citation_signature","submit_replication":"https://pith.science/pith/52ZJU3KST7V3BKJ5WCFKBB5JPQ/action/replication_record"}},"created_at":"2026-07-05T01:35:00.278716+00:00","updated_at":"2026-07-05T01:35:00.278716+00:00"}