{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:IMVDUAZVRZPEX3X2HW525TQRK5","short_pith_number":"pith:IMVDUAZV","schema_version":"1.0","canonical_sha256":"432a3a03358e5e4beefa3dbbaece115761eb08913a2b896afd6a0f9c1d37b434","source":{"kind":"arxiv","id":"2001.02090","version":1},"attestation_state":"computed","paper":{"title":"AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Joosung Lee, Junhyeop Lee, Kyungjae Lee, Sangwon Hwang, Sangyoun Lee, Tae-young Chung, Woo Jin Kim","submitted_at":"2020-01-07T15:01:57Z","abstract_excerpt":"Visual odometry is an essential key for a localization module in SLAM systems. However, previous methods require tuning the system to adapt environment changes. In this paper, we propose a learning-based approach for frame-to-frame monocular visual odometry estimation. The proposed network is only learned by disparity maps for not only covering the environment changes but also solving the scale problem. Furthermore, attention block and skip-ordering scheme are introduced to achieve robust performance in various driving environment. Our network is compared with the conventional methods which us"},"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":"2001.02090","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-01-07T15:01:57Z","cross_cats_sorted":[],"title_canon_sha256":"f1345b99a11c3570ed34b0a39d001c471e2f0c08dc9281eeaee42cafd068d4ac","abstract_canon_sha256":"aff8ae38d04376bc9dbaacd9dc1a92383f091654fd019f63ec6b1fec1cfe74c2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:30:43.979388Z","signature_b64":"pxh5BcLIXJDzf6mo12PEWzaEW26qm6GG7FoD/EKFyM8YM0GQkZURNgAybk56l0VOmpByld+qYjphF6WuvIXACA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"432a3a03358e5e4beefa3dbbaece115761eb08913a2b896afd6a0f9c1d37b434","last_reissued_at":"2026-07-05T00:30:43.978960Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:30:43.978960Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Joosung Lee, Junhyeop Lee, Kyungjae Lee, Sangwon Hwang, Sangyoun Lee, Tae-young Chung, Woo Jin Kim","submitted_at":"2020-01-07T15:01:57Z","abstract_excerpt":"Visual odometry is an essential key for a localization module in SLAM systems. However, previous methods require tuning the system to adapt environment changes. In this paper, we propose a learning-based approach for frame-to-frame monocular visual odometry estimation. The proposed network is only learned by disparity maps for not only covering the environment changes but also solving the scale problem. Furthermore, attention block and skip-ordering scheme are introduced to achieve robust performance in various driving environment. Our network is compared with the conventional methods which us"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.02090","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/2001.02090/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":"2001.02090","created_at":"2026-07-05T00:30:43.979026+00:00"},{"alias_kind":"arxiv_version","alias_value":"2001.02090v1","created_at":"2026-07-05T00:30:43.979026+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.02090","created_at":"2026-07-05T00:30:43.979026+00:00"},{"alias_kind":"pith_short_12","alias_value":"IMVDUAZVRZPE","created_at":"2026-07-05T00:30:43.979026+00:00"},{"alias_kind":"pith_short_16","alias_value":"IMVDUAZVRZPEX3X2","created_at":"2026-07-05T00:30:43.979026+00:00"},{"alias_kind":"pith_short_8","alias_value":"IMVDUAZV","created_at":"2026-07-05T00:30:43.979026+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/IMVDUAZVRZPEX3X2HW525TQRK5","json":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5.json","graph_json":"https://pith.science/api/pith-number/IMVDUAZVRZPEX3X2HW525TQRK5/graph.json","events_json":"https://pith.science/api/pith-number/IMVDUAZVRZPEX3X2HW525TQRK5/events.json","paper":"https://pith.science/paper/IMVDUAZV"},"agent_actions":{"view_html":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5","download_json":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5.json","view_paper":"https://pith.science/paper/IMVDUAZV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2001.02090&json=true","fetch_graph":"https://pith.science/api/pith-number/IMVDUAZVRZPEX3X2HW525TQRK5/graph.json","fetch_events":"https://pith.science/api/pith-number/IMVDUAZVRZPEX3X2HW525TQRK5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5/action/storage_attestation","attest_author":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5/action/author_attestation","sign_citation":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5/action/citation_signature","submit_replication":"https://pith.science/pith/IMVDUAZVRZPEX3X2HW525TQRK5/action/replication_record"}},"created_at":"2026-07-05T00:30:43.979026+00:00","updated_at":"2026-07-05T00:30:43.979026+00:00"}