{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4O6WFRTL4ZJLPY4QZJZJDWF4UQ","short_pith_number":"pith:4O6WFRTL","canonical_record":{"source":{"id":"1902.06222","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-17T08:40:48Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"bde0f84577470f85d069bff7959e8ddd5d6ee1316670ef64859fa80026921631","abstract_canon_sha256":"c058815c7ed54722353e7b2ae1b6d47f1247dbad4ea3a76ffa81336735372669"},"schema_version":"1.0"},"canonical_sha256":"e3bd62c66be652b7e390ca7291d8bca42c67606a9d833f37df3e1f98685c1d3d","source":{"kind":"arxiv","id":"1902.06222","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06222","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06222v1","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06222","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"pith_short_12","alias_value":"4O6WFRTL4ZJL","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4O6WFRTL4ZJLPY4Q","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4O6WFRTL","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4O6WFRTL4ZJLPY4QZJZJDWF4UQ","target":"record","payload":{"canonical_record":{"source":{"id":"1902.06222","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-17T08:40:48Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"bde0f84577470f85d069bff7959e8ddd5d6ee1316670ef64859fa80026921631","abstract_canon_sha256":"c058815c7ed54722353e7b2ae1b6d47f1247dbad4ea3a76ffa81336735372669"},"schema_version":"1.0"},"canonical_sha256":"e3bd62c66be652b7e390ca7291d8bca42c67606a9d833f37df3e1f98685c1d3d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:46.244710Z","signature_b64":"qYHM0dOD+QITDVeHtu35gpN5CFv/pHs1WQfplw3U6S24KVE33Y3fZCtVbVXoMrDFQdsprcfRvMYMr3/qD4CoDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3bd62c66be652b7e390ca7291d8bca42c67606a9d833f37df3e1f98685c1d3d","last_reissued_at":"2026-05-17T23:53:46.244071Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:46.244071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.06222","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":"2026-05-17T23:53:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bBaa9yyrUoWZFEQ7nCpgEm8MdfL5UoD8OIPtZN/PQONCmKITDlyWsCUOJ7ecFg6wE7+lxg1L2Vyn76kkhvEJCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T15:52:31.798738Z"},"content_sha256":"9d4a79dd3115d1a3b8746be68940f79cc30a8c0436e236c5bbde7950d0077e12","schema_version":"1.0","event_id":"sha256:9d4a79dd3115d1a3b8746be68940f79cc30a8c0436e236c5bbde7950d0077e12"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4O6WFRTL4ZJLPY4QZJZJDWF4UQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Denis Pellerin, Dong-Ming Yan, Kai Wang, Weize Quan, Xiaopeng Zhang","submitted_at":"2019-02-17T08:40:48Z","abstract_excerpt":"Image colorization achieves more and more realistic results with the increasing computation power of recent deep learning techniques. It becomes more difficult to identify the fake colorized images by human eyes. In this work, we propose a novel forensic method to distinguish between natural images (NIs) and colorized images (CIs) based on convolutional neural network (CNN). Our method is able to achieve high classification accuracy and cope with the challenging scenario of blind detection, i.e., no training sample is available from \"unknown\" colorization algorithm that we may encounter during"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06222","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":""},"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":"2026-05-17T23:53:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7CAqzvJf9DEDch5d+wzTBicw4ge1P/PResTIoYL/pmId0IjrKj1PsFwb9VhVqGlhp+dqTqj6Y7vReOKbkBx+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T15:52:31.799085Z"},"content_sha256":"46bfe838cc33ef78f0dec0d7679a20093c0a0115c5cfd49a6129a7fda29dcabb","schema_version":"1.0","event_id":"sha256:46bfe838cc33ef78f0dec0d7679a20093c0a0115c5cfd49a6129a7fda29dcabb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/bundle.json","state_url":"https://pith.science/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/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":"2026-06-09T15:52:31Z","links":{"resolver":"https://pith.science/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ","bundle":"https://pith.science/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/bundle.json","state":"https://pith.science/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4O6WFRTL4ZJLPY4QZJZJDWF4UQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4O6WFRTL4ZJLPY4QZJZJDWF4UQ","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":"c058815c7ed54722353e7b2ae1b6d47f1247dbad4ea3a76ffa81336735372669","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-17T08:40:48Z","title_canon_sha256":"bde0f84577470f85d069bff7959e8ddd5d6ee1316670ef64859fa80026921631"},"schema_version":"1.0","source":{"id":"1902.06222","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06222","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06222v1","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06222","created_at":"2026-05-17T23:53:46Z"},{"alias_kind":"pith_short_12","alias_value":"4O6WFRTL4ZJL","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4O6WFRTL4ZJLPY4Q","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4O6WFRTL","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:46bfe838cc33ef78f0dec0d7679a20093c0a0115c5cfd49a6129a7fda29dcabb","target":"graph","created_at":"2026-05-17T23:53:46Z","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"},"paper":{"abstract_excerpt":"Image colorization achieves more and more realistic results with the increasing computation power of recent deep learning techniques. It becomes more difficult to identify the fake colorized images by human eyes. In this work, we propose a novel forensic method to distinguish between natural images (NIs) and colorized images (CIs) based on convolutional neural network (CNN). Our method is able to achieve high classification accuracy and cope with the challenging scenario of blind detection, i.e., no training sample is available from \"unknown\" colorization algorithm that we may encounter during","authors_text":"Denis Pellerin, Dong-Ming Yan, Kai Wang, Weize Quan, Xiaopeng Zhang","cross_cats":["cs.LG","eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-17T08:40:48Z","title":"Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06222","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":"sha256:9d4a79dd3115d1a3b8746be68940f79cc30a8c0436e236c5bbde7950d0077e12","target":"record","created_at":"2026-05-17T23:53:46Z","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":"c058815c7ed54722353e7b2ae1b6d47f1247dbad4ea3a76ffa81336735372669","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-17T08:40:48Z","title_canon_sha256":"bde0f84577470f85d069bff7959e8ddd5d6ee1316670ef64859fa80026921631"},"schema_version":"1.0","source":{"id":"1902.06222","kind":"arxiv","version":1}},"canonical_sha256":"e3bd62c66be652b7e390ca7291d8bca42c67606a9d833f37df3e1f98685c1d3d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3bd62c66be652b7e390ca7291d8bca42c67606a9d833f37df3e1f98685c1d3d","first_computed_at":"2026-05-17T23:53:46.244071Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:46.244071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qYHM0dOD+QITDVeHtu35gpN5CFv/pHs1WQfplw3U6S24KVE33Y3fZCtVbVXoMrDFQdsprcfRvMYMr3/qD4CoDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:46.244710Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06222","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d4a79dd3115d1a3b8746be68940f79cc30a8c0436e236c5bbde7950d0077e12","sha256:46bfe838cc33ef78f0dec0d7679a20093c0a0115c5cfd49a6129a7fda29dcabb"],"state_sha256":"4e8ffb19c282f0ec60b7ceecdc871b2b916d8a3e6f36974260d713135e564e34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aw6Ap/WXYoRhXW32blsxvdOZ+zd4tfKzrz7A47uSCIDVCC04cu3WZvTjzyj3MrjdHuYCSl6vfcmq/iVfZo6ADg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T15:52:31.801052Z","bundle_sha256":"17efe7433dc3e09c13e22e279e11ef69c5a3aca288a9797b80dcbc9809a08f61"}}