{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:3Q4QJLKTQWRFQOQC2HGS34SJHQ","short_pith_number":"pith:3Q4QJLKT","schema_version":"1.0","canonical_sha256":"dc3904ad5385a2583a02d1cd2df2493c2ebf95787799625c1e11f2a1a3458ca5","source":{"kind":"arxiv","id":"2501.05555","version":2},"attestation_state":"computed","paper":{"title":"Improving Zero-Shot Object-Level Change Detection by Incorporating Visual Correspondence","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Anh Totti Nguyen, Hung Huy Nguyen, Long Mai, Pooyan Rahmanzadehgervi","submitted_at":"2025-01-09T20:02:10Z","abstract_excerpt":"Detecting object-level changes between two images across possibly different views is a core task in many applications that involve visual inspection or camera surveillance. Existing change-detection approaches suffer from three major limitations: (1) lack of evaluation on image pairs that contain no changes, leading to unreported false positive rates; (2) lack of correspondences (i.e., localizing the regions before and after a change); and (3) poor zero-shot generalization across different domains. To address these issues, we introduce a novel method that leverages change correspondences (a) d"},"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":"2501.05555","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-09T20:02:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6093f5bfcbfdf5fe9579897f74bc6e44cb5cd50def47c95940a1ccbc5cde084b","abstract_canon_sha256":"1ae97adf17b405dd0bdaf7ab4d4c61296837cd629506e6a34185fe6fc1c249e0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:01:38.945479Z","signature_b64":"fRESPjgfEolbD7O2BJ9BXR+e8ur3mdJ6wHXp5Ihz0kePMvJ/u3YmUGkbnIoYUH4UXz5RcKg61DW+tlcEtPIMBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc3904ad5385a2583a02d1cd2df2493c2ebf95787799625c1e11f2a1a3458ca5","last_reissued_at":"2026-07-05T10:01:38.945060Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:01:38.945060Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improving Zero-Shot Object-Level Change Detection by Incorporating Visual Correspondence","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Anh Totti Nguyen, Hung Huy Nguyen, Long Mai, Pooyan Rahmanzadehgervi","submitted_at":"2025-01-09T20:02:10Z","abstract_excerpt":"Detecting object-level changes between two images across possibly different views is a core task in many applications that involve visual inspection or camera surveillance. Existing change-detection approaches suffer from three major limitations: (1) lack of evaluation on image pairs that contain no changes, leading to unreported false positive rates; (2) lack of correspondences (i.e., localizing the regions before and after a change); and (3) poor zero-shot generalization across different domains. To address these issues, we introduce a novel method that leverages change correspondences (a) d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05555","kind":"arxiv","version":2},"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/2501.05555/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":"2501.05555","created_at":"2026-07-05T10:01:38.945119+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.05555v2","created_at":"2026-07-05T10:01:38.945119+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.05555","created_at":"2026-07-05T10:01:38.945119+00:00"},{"alias_kind":"pith_short_12","alias_value":"3Q4QJLKTQWRF","created_at":"2026-07-05T10:01:38.945119+00:00"},{"alias_kind":"pith_short_16","alias_value":"3Q4QJLKTQWRFQOQC","created_at":"2026-07-05T10:01:38.945119+00:00"},{"alias_kind":"pith_short_8","alias_value":"3Q4QJLKT","created_at":"2026-07-05T10:01:38.945119+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/3Q4QJLKTQWRFQOQC2HGS34SJHQ","json":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ.json","graph_json":"https://pith.science/api/pith-number/3Q4QJLKTQWRFQOQC2HGS34SJHQ/graph.json","events_json":"https://pith.science/api/pith-number/3Q4QJLKTQWRFQOQC2HGS34SJHQ/events.json","paper":"https://pith.science/paper/3Q4QJLKT"},"agent_actions":{"view_html":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ","download_json":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ.json","view_paper":"https://pith.science/paper/3Q4QJLKT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.05555&json=true","fetch_graph":"https://pith.science/api/pith-number/3Q4QJLKTQWRFQOQC2HGS34SJHQ/graph.json","fetch_events":"https://pith.science/api/pith-number/3Q4QJLKTQWRFQOQC2HGS34SJHQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ/action/storage_attestation","attest_author":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ/action/author_attestation","sign_citation":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ/action/citation_signature","submit_replication":"https://pith.science/pith/3Q4QJLKTQWRFQOQC2HGS34SJHQ/action/replication_record"}},"created_at":"2026-07-05T10:01:38.945119+00:00","updated_at":"2026-07-05T10:01:38.945119+00:00"}