{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:W3F4VZ4Y54YIHWDBO6BQ543URL","short_pith_number":"pith:W3F4VZ4Y","schema_version":"1.0","canonical_sha256":"b6cbcae798ef3083d86177830ef3748afc8a1e5e3249a64613f29594a0886ed0","source":{"kind":"arxiv","id":"2309.09306","version":1},"attestation_state":"computed","paper":{"title":"Effective Image Tampering Localization via Enhanced Transformer and Co-attention Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.CV","authors_text":"Gang Cao, Haochen Zhu, Kun Guo","submitted_at":"2023-09-17T15:43:06Z","abstract_excerpt":"Powerful manipulation techniques have made digital image forgeries be easily created and widespread without leaving visual anomalies. The blind localization of tampered regions becomes quite significant for image forensics. In this paper, we propose an effective image tampering localization network (EITLNet) based on a two-branch enhanced transformer encoder with attention-based feature fusion. Specifically, a feature enhancement module is designed to enhance the feature representation ability of the transformer encoder. The features extracted from RGB and noise streams are fused effectively b"},"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":"2309.09306","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-17T15:43:06Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"cb31813ae4705f82861a7844db467c0c6e75649d0da9becff24895826ab2aa6c","abstract_canon_sha256":"26304b82ad5300af2307b457a880c22a164dd4e18ca2f384714edacf83d25e4e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:51:37.156741Z","signature_b64":"ZycMYV2Yj2BEvsqQrQ9vmQ3+aNzr4iEkPLBCp9X8meqlAs2w+HochIQ2InGspXRIDE2IxrCCidlPY3QS/V2mDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6cbcae798ef3083d86177830ef3748afc8a1e5e3249a64613f29594a0886ed0","last_reissued_at":"2026-07-05T06:51:37.156359Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:51:37.156359Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Effective Image Tampering Localization via Enhanced Transformer and Co-attention Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.CV","authors_text":"Gang Cao, Haochen Zhu, Kun Guo","submitted_at":"2023-09-17T15:43:06Z","abstract_excerpt":"Powerful manipulation techniques have made digital image forgeries be easily created and widespread without leaving visual anomalies. The blind localization of tampered regions becomes quite significant for image forensics. In this paper, we propose an effective image tampering localization network (EITLNet) based on a two-branch enhanced transformer encoder with attention-based feature fusion. Specifically, a feature enhancement module is designed to enhance the feature representation ability of the transformer encoder. The features extracted from RGB and noise streams are fused effectively b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.09306","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/2309.09306/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":"2309.09306","created_at":"2026-07-05T06:51:37.156411+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.09306v1","created_at":"2026-07-05T06:51:37.156411+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.09306","created_at":"2026-07-05T06:51:37.156411+00:00"},{"alias_kind":"pith_short_12","alias_value":"W3F4VZ4Y54YI","created_at":"2026-07-05T06:51:37.156411+00:00"},{"alias_kind":"pith_short_16","alias_value":"W3F4VZ4Y54YIHWDB","created_at":"2026-07-05T06:51:37.156411+00:00"},{"alias_kind":"pith_short_8","alias_value":"W3F4VZ4Y","created_at":"2026-07-05T06:51:37.156411+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/W3F4VZ4Y54YIHWDBO6BQ543URL","json":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL.json","graph_json":"https://pith.science/api/pith-number/W3F4VZ4Y54YIHWDBO6BQ543URL/graph.json","events_json":"https://pith.science/api/pith-number/W3F4VZ4Y54YIHWDBO6BQ543URL/events.json","paper":"https://pith.science/paper/W3F4VZ4Y"},"agent_actions":{"view_html":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL","download_json":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL.json","view_paper":"https://pith.science/paper/W3F4VZ4Y","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.09306&json=true","fetch_graph":"https://pith.science/api/pith-number/W3F4VZ4Y54YIHWDBO6BQ543URL/graph.json","fetch_events":"https://pith.science/api/pith-number/W3F4VZ4Y54YIHWDBO6BQ543URL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL/action/storage_attestation","attest_author":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL/action/author_attestation","sign_citation":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL/action/citation_signature","submit_replication":"https://pith.science/pith/W3F4VZ4Y54YIHWDBO6BQ543URL/action/replication_record"}},"created_at":"2026-07-05T06:51:37.156411+00:00","updated_at":"2026-07-05T06:51:37.156411+00:00"}