{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QVUMJTUT52VTQIGL2SZ53TODRR","short_pith_number":"pith:QVUMJTUT","schema_version":"1.0","canonical_sha256":"8568c4ce93eeab3820cbd4b3ddcdc38c532aa5f043f7334728b6ac677b1ff90d","source":{"kind":"arxiv","id":"2306.15010","version":3},"attestation_state":"computed","paper":{"title":"Efficient High-Resolution Template Matching with Vector Quantized Nearest Neighbour Fields","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CV","authors_text":"Ankit Gupta, Ida-Maria Sintorn","submitted_at":"2023-06-26T18:49:09Z","abstract_excerpt":"Template matching is a fundamental problem in computer vision with applications in fields including object detection, image registration, and object tracking. Current methods rely on nearest-neighbour (NN) matching, where the query feature space is converted to NN space by representing each query pixel with its NN in the template. NN-based methods have been shown to perform better in occlusions, appearance changes, and non-rigid transformations; however, they scale poorly with high-resolution data and high feature dimensions. We present an NN-based method which efficiently reduces the NN compu"},"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":"2306.15010","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-06-26T18:49:09Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"fb326475e1407b2f93cf9884b78dde33942d1905a9b21275d8760e7e6a136b56","abstract_canon_sha256":"39916169641e196190a2a98a56c3c70cc31263a28ecfe5cae0818f2c663132b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:01:42.865942Z","signature_b64":"lAE9uVe7b6MvKvRxl5Vg+DhO5Rvo8e+lI9UM9DtrxjuhJShct19fp3RRuIDycHqdUa6aSDHNSs84vgBtjmY9Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8568c4ce93eeab3820cbd4b3ddcdc38c532aa5f043f7334728b6ac677b1ff90d","last_reissued_at":"2026-07-05T07:01:42.865483Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:01:42.865483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient High-Resolution Template Matching with Vector Quantized Nearest Neighbour Fields","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CV","authors_text":"Ankit Gupta, Ida-Maria Sintorn","submitted_at":"2023-06-26T18:49:09Z","abstract_excerpt":"Template matching is a fundamental problem in computer vision with applications in fields including object detection, image registration, and object tracking. Current methods rely on nearest-neighbour (NN) matching, where the query feature space is converted to NN space by representing each query pixel with its NN in the template. NN-based methods have been shown to perform better in occlusions, appearance changes, and non-rigid transformations; however, they scale poorly with high-resolution data and high feature dimensions. We present an NN-based method which efficiently reduces the NN compu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.15010","kind":"arxiv","version":3},"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/2306.15010/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":"2306.15010","created_at":"2026-07-05T07:01:42.865541+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.15010v3","created_at":"2026-07-05T07:01:42.865541+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.15010","created_at":"2026-07-05T07:01:42.865541+00:00"},{"alias_kind":"pith_short_12","alias_value":"QVUMJTUT52VT","created_at":"2026-07-05T07:01:42.865541+00:00"},{"alias_kind":"pith_short_16","alias_value":"QVUMJTUT52VTQIGL","created_at":"2026-07-05T07:01:42.865541+00:00"},{"alias_kind":"pith_short_8","alias_value":"QVUMJTUT","created_at":"2026-07-05T07:01:42.865541+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/QVUMJTUT52VTQIGL2SZ53TODRR","json":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR.json","graph_json":"https://pith.science/api/pith-number/QVUMJTUT52VTQIGL2SZ53TODRR/graph.json","events_json":"https://pith.science/api/pith-number/QVUMJTUT52VTQIGL2SZ53TODRR/events.json","paper":"https://pith.science/paper/QVUMJTUT"},"agent_actions":{"view_html":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR","download_json":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR.json","view_paper":"https://pith.science/paper/QVUMJTUT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.15010&json=true","fetch_graph":"https://pith.science/api/pith-number/QVUMJTUT52VTQIGL2SZ53TODRR/graph.json","fetch_events":"https://pith.science/api/pith-number/QVUMJTUT52VTQIGL2SZ53TODRR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR/action/storage_attestation","attest_author":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR/action/author_attestation","sign_citation":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR/action/citation_signature","submit_replication":"https://pith.science/pith/QVUMJTUT52VTQIGL2SZ53TODRR/action/replication_record"}},"created_at":"2026-07-05T07:01:42.865541+00:00","updated_at":"2026-07-05T07:01:42.865541+00:00"}