{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TBCJODTW7SGBH7WG4KEYX25UNL","short_pith_number":"pith:TBCJODTW","canonical_record":{"source":{"id":"2407.00226","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-28T20:42:36Z","cross_cats_sorted":[],"title_canon_sha256":"bd333edb3a7303c8254e1671b5d95bd2f74a0522fe26942a3637184405ada853","abstract_canon_sha256":"3ec095198bd1757efb88efa670d845d9d8fdfdfe17216b86ff39089d276e69ce"},"schema_version":"1.0"},"canonical_sha256":"9844970e76fc8c13fec6e2898bebb46affdb19521e447e073b0c78a09b0dffec","source":{"kind":"arxiv","id":"2407.00226","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.00226","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"arxiv_version","alias_value":"2407.00226v1","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.00226","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_12","alias_value":"TBCJODTW7SGB","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_16","alias_value":"TBCJODTW7SGBH7WG","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_8","alias_value":"TBCJODTW","created_at":"2026-07-05T10:10:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TBCJODTW7SGBH7WG4KEYX25UNL","target":"record","payload":{"canonical_record":{"source":{"id":"2407.00226","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-28T20:42:36Z","cross_cats_sorted":[],"title_canon_sha256":"bd333edb3a7303c8254e1671b5d95bd2f74a0522fe26942a3637184405ada853","abstract_canon_sha256":"3ec095198bd1757efb88efa670d845d9d8fdfdfe17216b86ff39089d276e69ce"},"schema_version":"1.0"},"canonical_sha256":"9844970e76fc8c13fec6e2898bebb46affdb19521e447e073b0c78a09b0dffec","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:10:07.962845Z","signature_b64":"Mj1NptRLc1wozqbyU7ch6JRqTc10jNfMhOawVjIUJEMbNs+T3GPs5ov9Ht9eYW6JR3qV+RGyevo3aoX//KjBCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9844970e76fc8c13fec6e2898bebb46affdb19521e447e073b0c78a09b0dffec","last_reissued_at":"2026-07-05T10:10:07.962494Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:10:07.962494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.00226","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:10:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c8CrBZY3DCY906koGxTaipcf+tausAOeRvBmDK+3CZS469uVwcw/40S5oBDOylMHOTyasoi//gb38NUiiPt2Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T10:40:44.038277Z"},"content_sha256":"97b5cd3f41fc10e7af90b5ef4d710aa3c884c7ee56fded86dea0a9c4cc568f8e","schema_version":"1.0","event_id":"sha256:97b5cd3f41fc10e7af90b5ef4d710aa3c884c7ee56fded86dea0a9c4cc568f8e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TBCJODTW7SGBH7WG4KEYX25UNL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transformer-based Image and Video Inpainting: Current Challenges and Future Directions","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abdelkader Nasreddine Belkacem, Abderrahmane Lakas, Elarbi Badidi, Omar Elharrouss, Rafat Damseh","submitted_at":"2024-06-28T20:42:36Z","abstract_excerpt":"Image inpainting is currently a hot topic within the field of computer vision. It offers a viable solution for various applications, including photographic restoration, video editing, and medical imaging. Deep learning advancements, notably convolutional neural networks (CNNs) and generative adversarial networks (GANs), have significantly enhanced the inpainting task with an improved capability to fill missing or damaged regions in an image or video through the incorporation of contextually appropriate details. These advancements have improved other aspects, including efficiency, information p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.00226","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/2407.00226/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:10:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MjPpcUtmCjjqNGDojMdYrOl1XW2pI9w+RLYv5b+5I1fVy1OR+jg7Zb6ogVDBnzn3g6u9Y22wO/8VRuWI2LXiCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T10:40:44.038947Z"},"content_sha256":"21a69cab23e77a715014f6399780f6fb1673429064ceb11978a2ee90ae7807aa","schema_version":"1.0","event_id":"sha256:21a69cab23e77a715014f6399780f6fb1673429064ceb11978a2ee90ae7807aa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TBCJODTW7SGBH7WG4KEYX25UNL/bundle.json","state_url":"https://pith.science/pith/TBCJODTW7SGBH7WG4KEYX25UNL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TBCJODTW7SGBH7WG4KEYX25UNL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-14T10:40:44Z","links":{"resolver":"https://pith.science/pith/TBCJODTW7SGBH7WG4KEYX25UNL","bundle":"https://pith.science/pith/TBCJODTW7SGBH7WG4KEYX25UNL/bundle.json","state":"https://pith.science/pith/TBCJODTW7SGBH7WG4KEYX25UNL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TBCJODTW7SGBH7WG4KEYX25UNL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TBCJODTW7SGBH7WG4KEYX25UNL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3ec095198bd1757efb88efa670d845d9d8fdfdfe17216b86ff39089d276e69ce","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-28T20:42:36Z","title_canon_sha256":"bd333edb3a7303c8254e1671b5d95bd2f74a0522fe26942a3637184405ada853"},"schema_version":"1.0","source":{"id":"2407.00226","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.00226","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"arxiv_version","alias_value":"2407.00226v1","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.00226","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_12","alias_value":"TBCJODTW7SGB","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_16","alias_value":"TBCJODTW7SGBH7WG","created_at":"2026-07-05T10:10:07Z"},{"alias_kind":"pith_short_8","alias_value":"TBCJODTW","created_at":"2026-07-05T10:10:07Z"}],"graph_snapshots":[{"event_id":"sha256:21a69cab23e77a715014f6399780f6fb1673429064ceb11978a2ee90ae7807aa","target":"graph","created_at":"2026-07-05T10:10:07Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2407.00226/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image inpainting is currently a hot topic within the field of computer vision. It offers a viable solution for various applications, including photographic restoration, video editing, and medical imaging. Deep learning advancements, notably convolutional neural networks (CNNs) and generative adversarial networks (GANs), have significantly enhanced the inpainting task with an improved capability to fill missing or damaged regions in an image or video through the incorporation of contextually appropriate details. These advancements have improved other aspects, including efficiency, information p","authors_text":"Abdelkader Nasreddine Belkacem, Abderrahmane Lakas, Elarbi Badidi, Omar Elharrouss, Rafat Damseh","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-28T20:42:36Z","title":"Transformer-based Image and Video Inpainting: Current Challenges and Future Directions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.00226","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:97b5cd3f41fc10e7af90b5ef4d710aa3c884c7ee56fded86dea0a9c4cc568f8e","target":"record","created_at":"2026-07-05T10:10:07Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3ec095198bd1757efb88efa670d845d9d8fdfdfe17216b86ff39089d276e69ce","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-28T20:42:36Z","title_canon_sha256":"bd333edb3a7303c8254e1671b5d95bd2f74a0522fe26942a3637184405ada853"},"schema_version":"1.0","source":{"id":"2407.00226","kind":"arxiv","version":1}},"canonical_sha256":"9844970e76fc8c13fec6e2898bebb46affdb19521e447e073b0c78a09b0dffec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9844970e76fc8c13fec6e2898bebb46affdb19521e447e073b0c78a09b0dffec","first_computed_at":"2026-07-05T10:10:07.962494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:10:07.962494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mj1NptRLc1wozqbyU7ch6JRqTc10jNfMhOawVjIUJEMbNs+T3GPs5ov9Ht9eYW6JR3qV+RGyevo3aoX//KjBCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:10:07.962845Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.00226","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:97b5cd3f41fc10e7af90b5ef4d710aa3c884c7ee56fded86dea0a9c4cc568f8e","sha256:21a69cab23e77a715014f6399780f6fb1673429064ceb11978a2ee90ae7807aa"],"state_sha256":"3d4aaf55b7313401e9ff423547e70724a6f0c6506eff60559bd337ea99c548f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9CkDPZdcznnFCBx0Lf6G8uaQseuOZF7DI94bIfwcy3H2BcuV/SxApCzeu09oEXDuAQ+MqPvQOqj6eEXISl2qCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T10:40:44.043317Z","bundle_sha256":"40dea8654f6fac64533f2639bb1ed094ca46db40459ca782a71c55544e6056c6"}}