{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:3UXAPLKSW4IBJBAUH24TWAZQSZ","short_pith_number":"pith:3UXAPLKS","schema_version":"1.0","canonical_sha256":"dd2e07ad52b7101484143eb93b03309662f73a5a0585a7cbf9f6354d0c4ef1fc","source":{"kind":"arxiv","id":"2012.10902","version":1},"attestation_state":"computed","paper":{"title":"Learning to Localize Using a LiDAR Intensity Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"Andrei Pokrovsky, Ioan Andrei B\\^arsan, Raquel Urtasun, Shenlong Wang","submitted_at":"2020-12-20T11:56:23Z","abstract_excerpt":"In this paper we propose a real-time, calibration-agnostic and effective localization system for self-driving cars. Our method learns to embed the online LiDAR sweeps and intensity map into a joint deep embedding space. Localization is then conducted through an efficient convolutional matching between the embeddings. Our full system can operate in real-time at 15Hz while achieving centimeter level accuracy across different LiDAR sensors and environments. Our experiments illustrate the performance of the proposed approach over a large-scale dataset consisting of over 4000km of driving."},"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":"2012.10902","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-20T11:56:23Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"6cadc5a94986fa20b5eaabc123313f142a73881971d5a6cfa75213aafefa35a5","abstract_canon_sha256":"0ce29f91ede7b95d2dc7dae66ae4fe4a761f4464370f32b069af194dc48eb807"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:00:56.726772Z","signature_b64":"ymWHBGcH4UdShhrC9eoZ4tO+Bg1wdmPcLjwzTOUz68DRnQYuHb0YaodJIntgZZxNXuMKJ+qKo6UecBWkNnf0Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd2e07ad52b7101484143eb93b03309662f73a5a0585a7cbf9f6354d0c4ef1fc","last_reissued_at":"2026-07-05T02:00:56.726395Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:00:56.726395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning to Localize Using a LiDAR Intensity Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"Andrei Pokrovsky, Ioan Andrei B\\^arsan, Raquel Urtasun, Shenlong Wang","submitted_at":"2020-12-20T11:56:23Z","abstract_excerpt":"In this paper we propose a real-time, calibration-agnostic and effective localization system for self-driving cars. Our method learns to embed the online LiDAR sweeps and intensity map into a joint deep embedding space. Localization is then conducted through an efficient convolutional matching between the embeddings. Our full system can operate in real-time at 15Hz while achieving centimeter level accuracy across different LiDAR sensors and environments. Our experiments illustrate the performance of the proposed approach over a large-scale dataset consisting of over 4000km of driving."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.10902","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/2012.10902/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":"2012.10902","created_at":"2026-07-05T02:00:56.726452+00:00"},{"alias_kind":"arxiv_version","alias_value":"2012.10902v1","created_at":"2026-07-05T02:00:56.726452+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.10902","created_at":"2026-07-05T02:00:56.726452+00:00"},{"alias_kind":"pith_short_12","alias_value":"3UXAPLKSW4IB","created_at":"2026-07-05T02:00:56.726452+00:00"},{"alias_kind":"pith_short_16","alias_value":"3UXAPLKSW4IBJBAU","created_at":"2026-07-05T02:00:56.726452+00:00"},{"alias_kind":"pith_short_8","alias_value":"3UXAPLKS","created_at":"2026-07-05T02:00:56.726452+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/3UXAPLKSW4IBJBAUH24TWAZQSZ","json":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ.json","graph_json":"https://pith.science/api/pith-number/3UXAPLKSW4IBJBAUH24TWAZQSZ/graph.json","events_json":"https://pith.science/api/pith-number/3UXAPLKSW4IBJBAUH24TWAZQSZ/events.json","paper":"https://pith.science/paper/3UXAPLKS"},"agent_actions":{"view_html":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ","download_json":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ.json","view_paper":"https://pith.science/paper/3UXAPLKS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2012.10902&json=true","fetch_graph":"https://pith.science/api/pith-number/3UXAPLKSW4IBJBAUH24TWAZQSZ/graph.json","fetch_events":"https://pith.science/api/pith-number/3UXAPLKSW4IBJBAUH24TWAZQSZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ/action/storage_attestation","attest_author":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ/action/author_attestation","sign_citation":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ/action/citation_signature","submit_replication":"https://pith.science/pith/3UXAPLKSW4IBJBAUH24TWAZQSZ/action/replication_record"}},"created_at":"2026-07-05T02:00:56.726452+00:00","updated_at":"2026-07-05T02:00:56.726452+00:00"}