{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:U7GOP2EMEYNB7QUZEQTMVNU7JT","short_pith_number":"pith:U7GOP2EM","canonical_record":{"source":{"id":"2104.06832","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-14T13:05:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f0ecd72acb3b750418dc0a36b80e0bcef0c577c43b9a543166f51937bc596802","abstract_canon_sha256":"cb83a564f727a57a0ad56d81e93c3035178d5d01cdba16111d26054a15c1585a"},"schema_version":"1.0"},"canonical_sha256":"a7cce7e88c261a1fc2992426cab69f4cf828dbe5b594a1918a5a09b17f819264","source":{"kind":"arxiv","id":"2104.06832","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06832","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06832v2","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06832","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_12","alias_value":"U7GOP2EMEYNB","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_16","alias_value":"U7GOP2EMEYNB7QUZ","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_8","alias_value":"U7GOP2EM","created_at":"2026-07-05T03:00:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:U7GOP2EMEYNB7QUZEQTMVNU7JT","target":"record","payload":{"canonical_record":{"source":{"id":"2104.06832","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-14T13:05:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f0ecd72acb3b750418dc0a36b80e0bcef0c577c43b9a543166f51937bc596802","abstract_canon_sha256":"cb83a564f727a57a0ad56d81e93c3035178d5d01cdba16111d26054a15c1585a"},"schema_version":"1.0"},"canonical_sha256":"a7cce7e88c261a1fc2992426cab69f4cf828dbe5b594a1918a5a09b17f819264","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:00:32.835822Z","signature_b64":"vAivZ7wfD+Yhxd8WV6e+HWccz7SKpnug/t8OY1pV8A+WUrHGOBNtwOrmSm0QHeNTFMReO9+GKf+bzh/uhEBrCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7cce7e88c261a1fc2992426cab69f4cf828dbe5b594a1918a5a09b17f819264","last_reissued_at":"2026-07-05T03:00:32.835393Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:00:32.835393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.06832","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:00:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wwAge5f1yQTqN6zNMdhJo2y3SQggdo0cVK895qA6IxyvT5u7agVgJPctJxra8HV8FPLZe4CrA6TGoGv5XSkfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T15:59:51.886596Z"},"content_sha256":"bdfdd6c58bc2e8668f191c269c5e5d221162ae77bf0f3a316ad2cb258b14adfa","schema_version":"1.0","event_id":"sha256:bdfdd6c58bc2e8668f191c269c5e5d221162ae77bf0f3a316ad2cb258b14adfa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:U7GOP2EMEYNB7QUZEQTMVNU7JT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Image Manipulation Detection by Multi-View Multi-Scale Supervision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chengbo Dong, Jiaqi Ji, Juan Cao, Xinru Chen, Xirong Li","submitted_at":"2021-04-14T13:05:58Z","abstract_excerpt":"The key challenge of image manipulation detection is how to learn generalizable features that are sensitive to manipulations in novel data, whilst specific to prevent false alarms on authentic images. Current research emphasizes the sensitivity, with the specificity overlooked. In this paper we address both aspects by multi-view feature learning and multi-scale supervision. By exploiting noise distribution and boundary artifact surrounding tampered regions, the former aims to learn semantic-agnostic and thus more generalizable features. The latter allows us to learn from authentic images which"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06832","kind":"arxiv","version":2},"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/2104.06832/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":"2026-07-05T03:00:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VjCFhCQGGddF1RYzc0acS7HxjbM8vnuX5IIUfEAc8EqU6OYrJeEXnhopC5mWnyV0pA5+LAF3SPinmnhf+IH3Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T15:59:51.886985Z"},"content_sha256":"5ca83b4b8a707a2455290f55aeae4618bc56fd7fed106fca8bd5df2fa72ccb8a","schema_version":"1.0","event_id":"sha256:5ca83b4b8a707a2455290f55aeae4618bc56fd7fed106fca8bd5df2fa72ccb8a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/bundle.json","state_url":"https://pith.science/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/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":"2026-07-07T15:59:51Z","links":{"resolver":"https://pith.science/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT","bundle":"https://pith.science/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/bundle.json","state":"https://pith.science/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U7GOP2EMEYNB7QUZEQTMVNU7JT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:U7GOP2EMEYNB7QUZEQTMVNU7JT","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":"cb83a564f727a57a0ad56d81e93c3035178d5d01cdba16111d26054a15c1585a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-14T13:05:58Z","title_canon_sha256":"f0ecd72acb3b750418dc0a36b80e0bcef0c577c43b9a543166f51937bc596802"},"schema_version":"1.0","source":{"id":"2104.06832","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06832","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06832v2","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06832","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_12","alias_value":"U7GOP2EMEYNB","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_16","alias_value":"U7GOP2EMEYNB7QUZ","created_at":"2026-07-05T03:00:32Z"},{"alias_kind":"pith_short_8","alias_value":"U7GOP2EM","created_at":"2026-07-05T03:00:32Z"}],"graph_snapshots":[{"event_id":"sha256:5ca83b4b8a707a2455290f55aeae4618bc56fd7fed106fca8bd5df2fa72ccb8a","target":"graph","created_at":"2026-07-05T03:00:32Z","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/2104.06832/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The key challenge of image manipulation detection is how to learn generalizable features that are sensitive to manipulations in novel data, whilst specific to prevent false alarms on authentic images. Current research emphasizes the sensitivity, with the specificity overlooked. In this paper we address both aspects by multi-view feature learning and multi-scale supervision. By exploiting noise distribution and boundary artifact surrounding tampered regions, the former aims to learn semantic-agnostic and thus more generalizable features. The latter allows us to learn from authentic images which","authors_text":"Chengbo Dong, Jiaqi Ji, Juan Cao, Xinru Chen, Xirong Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-14T13:05:58Z","title":"Image Manipulation Detection by Multi-View Multi-Scale Supervision"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06832","kind":"arxiv","version":2},"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:bdfdd6c58bc2e8668f191c269c5e5d221162ae77bf0f3a316ad2cb258b14adfa","target":"record","created_at":"2026-07-05T03:00:32Z","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":"cb83a564f727a57a0ad56d81e93c3035178d5d01cdba16111d26054a15c1585a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-14T13:05:58Z","title_canon_sha256":"f0ecd72acb3b750418dc0a36b80e0bcef0c577c43b9a543166f51937bc596802"},"schema_version":"1.0","source":{"id":"2104.06832","kind":"arxiv","version":2}},"canonical_sha256":"a7cce7e88c261a1fc2992426cab69f4cf828dbe5b594a1918a5a09b17f819264","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7cce7e88c261a1fc2992426cab69f4cf828dbe5b594a1918a5a09b17f819264","first_computed_at":"2026-07-05T03:00:32.835393Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:00:32.835393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vAivZ7wfD+Yhxd8WV6e+HWccz7SKpnug/t8OY1pV8A+WUrHGOBNtwOrmSm0QHeNTFMReO9+GKf+bzh/uhEBrCw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:00:32.835822Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.06832","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bdfdd6c58bc2e8668f191c269c5e5d221162ae77bf0f3a316ad2cb258b14adfa","sha256:5ca83b4b8a707a2455290f55aeae4618bc56fd7fed106fca8bd5df2fa72ccb8a"],"state_sha256":"f1ee728c5d56454597d0f80f0ef5cc44704b43ecd94cc4c65b7862b1924b8202"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R8VYArjHybgXRAFuapgpNhWMZywimO4FHasxyS0iX8ICuu4B1qsog6k5R0wSnUOq+YyuH6ySyQqWvU36FG5DBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T15:59:51.889426Z","bundle_sha256":"136a3185746cae6e9af9ac1cc13ed74c177b095b89a6def193e7835b14de9300"}}