{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:A3SHJ5HD7JD4WMNZFGKIBFOZFN","short_pith_number":"pith:A3SHJ5HD","schema_version":"1.0","canonical_sha256":"06e474f4e3fa47cb31b929948095d92b5682e9e33d91c3ac583254f46b4cd1f3","source":{"kind":"arxiv","id":"2508.00272","version":1},"attestation_state":"computed","paper":{"title":"Towards Robust Semantic Correspondence: A Benchmark and Insights","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Wenyue Chong","submitted_at":"2025-08-01T02:38:39Z","abstract_excerpt":"Semantic correspondence aims to identify semantically meaningful relationships between different images and is a fundamental challenge in computer vision. It forms the foundation for numerous tasks such as 3D reconstruction, object tracking, and image editing. With the progress of large-scale vision models, semantic correspondence has achieved remarkable performance in controlled and high-quality conditions. However, the robustness of semantic correspondence in challenging scenarios is much less investigated. In this work, we establish a novel benchmark for evaluating semantic correspondence i"},"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":"2508.00272","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-01T02:38:39Z","cross_cats_sorted":[],"title_canon_sha256":"7e37adcb7dd99eab72aae90aa10e52ed1f987ee719836d1aadfc8c61fd4f6f7f","abstract_canon_sha256":"73f94ce52f2d5d65d14c9e1a2a303cbea6e68e89eae6646c1b6a2f299a661105"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:46:52.327279Z","signature_b64":"mVdMy2Xbo3vNjmDsmvwbyV2S5EpfP+cvk+bdK3NSfUm2SkwZG/1sWYpAvk3cSfc91YQcH915CS/LZQuRtbyfCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"06e474f4e3fa47cb31b929948095d92b5682e9e33d91c3ac583254f46b4cd1f3","last_reissued_at":"2026-07-05T11:46:52.326832Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:46:52.326832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Robust Semantic Correspondence: A Benchmark and Insights","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Wenyue Chong","submitted_at":"2025-08-01T02:38:39Z","abstract_excerpt":"Semantic correspondence aims to identify semantically meaningful relationships between different images and is a fundamental challenge in computer vision. It forms the foundation for numerous tasks such as 3D reconstruction, object tracking, and image editing. With the progress of large-scale vision models, semantic correspondence has achieved remarkable performance in controlled and high-quality conditions. However, the robustness of semantic correspondence in challenging scenarios is much less investigated. In this work, we establish a novel benchmark for evaluating semantic correspondence i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.00272","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/2508.00272/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":"2508.00272","created_at":"2026-07-05T11:46:52.326887+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.00272v1","created_at":"2026-07-05T11:46:52.326887+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.00272","created_at":"2026-07-05T11:46:52.326887+00:00"},{"alias_kind":"pith_short_12","alias_value":"A3SHJ5HD7JD4","created_at":"2026-07-05T11:46:52.326887+00:00"},{"alias_kind":"pith_short_16","alias_value":"A3SHJ5HD7JD4WMNZ","created_at":"2026-07-05T11:46:52.326887+00:00"},{"alias_kind":"pith_short_8","alias_value":"A3SHJ5HD","created_at":"2026-07-05T11:46:52.326887+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/A3SHJ5HD7JD4WMNZFGKIBFOZFN","json":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN.json","graph_json":"https://pith.science/api/pith-number/A3SHJ5HD7JD4WMNZFGKIBFOZFN/graph.json","events_json":"https://pith.science/api/pith-number/A3SHJ5HD7JD4WMNZFGKIBFOZFN/events.json","paper":"https://pith.science/paper/A3SHJ5HD"},"agent_actions":{"view_html":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN","download_json":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN.json","view_paper":"https://pith.science/paper/A3SHJ5HD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.00272&json=true","fetch_graph":"https://pith.science/api/pith-number/A3SHJ5HD7JD4WMNZFGKIBFOZFN/graph.json","fetch_events":"https://pith.science/api/pith-number/A3SHJ5HD7JD4WMNZFGKIBFOZFN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN/action/storage_attestation","attest_author":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN/action/author_attestation","sign_citation":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN/action/citation_signature","submit_replication":"https://pith.science/pith/A3SHJ5HD7JD4WMNZFGKIBFOZFN/action/replication_record"}},"created_at":"2026-07-05T11:46:52.326887+00:00","updated_at":"2026-07-05T11:46:52.326887+00:00"}