{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:NH7TOGUXHJF5BNW7ATI2HYXQNH","short_pith_number":"pith:NH7TOGUX","schema_version":"1.0","canonical_sha256":"69ff371a973a4bd0b6df04d1a3e2f069c95294111eebe346d81f9c2dcd52d0cf","source":{"kind":"arxiv","id":"2303.02641","version":1},"attestation_state":"computed","paper":{"title":"CueCAn: Cue Driven Contextual Attention For Identifying Missing Traffic Signs on Unconstrained Roads","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Anbumani Subramanian, C.V. Jawahar, Rohit Saluja, Varun Gupta","submitted_at":"2023-03-05T11:06:20Z","abstract_excerpt":"Unconstrained Asian roads often involve poor infrastructure, affecting overall road safety. Missing traffic signs are a regular part of such roads. Missing or non-existing object detection has been studied for locating missing curbs and estimating reasonable regions for pedestrians on road scene images. Such methods involve analyzing task-specific single object cues. In this paper, we present the first and most challenging video dataset for missing objects, with multiple types of traffic signs for which the cues are visible without the signs in the scenes. We refer to it as the Missing Traffic"},"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":"2303.02641","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-05T11:06:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"931040612bf2123c6dd3f722f13599493160bb5199f0260c0a8823187157886c","abstract_canon_sha256":"c4002b4cd33f08e3a12272fc4d9d151fd2df2cb047bb47ce897a5511e2a7f601"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:48:13.541836Z","signature_b64":"WR1D7lj0uB1ylmC/0Pl0mhjS4cNK4QKHpH6t4DPD4t+MCZcRZSV8WqRgH+vFCwGRILmZPk4DwZOZOEKRQqoQAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69ff371a973a4bd0b6df04d1a3e2f069c95294111eebe346d81f9c2dcd52d0cf","last_reissued_at":"2026-07-05T05:48:13.541432Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:48:13.541432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CueCAn: Cue Driven Contextual Attention For Identifying Missing Traffic Signs on Unconstrained Roads","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Anbumani Subramanian, C.V. Jawahar, Rohit Saluja, Varun Gupta","submitted_at":"2023-03-05T11:06:20Z","abstract_excerpt":"Unconstrained Asian roads often involve poor infrastructure, affecting overall road safety. Missing traffic signs are a regular part of such roads. Missing or non-existing object detection has been studied for locating missing curbs and estimating reasonable regions for pedestrians on road scene images. Such methods involve analyzing task-specific single object cues. In this paper, we present the first and most challenging video dataset for missing objects, with multiple types of traffic signs for which the cues are visible without the signs in the scenes. We refer to it as the Missing Traffic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.02641","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/2303.02641/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":"2303.02641","created_at":"2026-07-05T05:48:13.541491+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.02641v1","created_at":"2026-07-05T05:48:13.541491+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.02641","created_at":"2026-07-05T05:48:13.541491+00:00"},{"alias_kind":"pith_short_12","alias_value":"NH7TOGUXHJF5","created_at":"2026-07-05T05:48:13.541491+00:00"},{"alias_kind":"pith_short_16","alias_value":"NH7TOGUXHJF5BNW7","created_at":"2026-07-05T05:48:13.541491+00:00"},{"alias_kind":"pith_short_8","alias_value":"NH7TOGUX","created_at":"2026-07-05T05:48:13.541491+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/NH7TOGUXHJF5BNW7ATI2HYXQNH","json":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH.json","graph_json":"https://pith.science/api/pith-number/NH7TOGUXHJF5BNW7ATI2HYXQNH/graph.json","events_json":"https://pith.science/api/pith-number/NH7TOGUXHJF5BNW7ATI2HYXQNH/events.json","paper":"https://pith.science/paper/NH7TOGUX"},"agent_actions":{"view_html":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH","download_json":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH.json","view_paper":"https://pith.science/paper/NH7TOGUX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.02641&json=true","fetch_graph":"https://pith.science/api/pith-number/NH7TOGUXHJF5BNW7ATI2HYXQNH/graph.json","fetch_events":"https://pith.science/api/pith-number/NH7TOGUXHJF5BNW7ATI2HYXQNH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH/action/storage_attestation","attest_author":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH/action/author_attestation","sign_citation":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH/action/citation_signature","submit_replication":"https://pith.science/pith/NH7TOGUXHJF5BNW7ATI2HYXQNH/action/replication_record"}},"created_at":"2026-07-05T05:48:13.541491+00:00","updated_at":"2026-07-05T05:48:13.541491+00:00"}