{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OHED6TMB7WR6L2F2DR7C6BHDEP","short_pith_number":"pith:OHED6TMB","canonical_record":{"source":{"id":"1811.01474","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-05T01:28:53Z","cross_cats_sorted":[],"title_canon_sha256":"5171d3220b3872392e194ea5d998703b288dee942498961999ac5a8a84d2fe95","abstract_canon_sha256":"8117d186ab338acd041ccf8cef8d225b7843c1b099919f0d6d8d1f9f6a6b55cb"},"schema_version":"1.0"},"canonical_sha256":"71c83f4d81fda3e5e8ba1c7e2f04e323f4664bfbe5129bf01f6975b4aedef0c3","source":{"kind":"arxiv","id":"1811.01474","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.01474","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"arxiv_version","alias_value":"1811.01474v3","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.01474","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"pith_short_12","alias_value":"OHED6TMB7WR6","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OHED6TMB7WR6L2F2","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OHED6TMB","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OHED6TMB7WR6L2F2DR7C6BHDEP","target":"record","payload":{"canonical_record":{"source":{"id":"1811.01474","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-05T01:28:53Z","cross_cats_sorted":[],"title_canon_sha256":"5171d3220b3872392e194ea5d998703b288dee942498961999ac5a8a84d2fe95","abstract_canon_sha256":"8117d186ab338acd041ccf8cef8d225b7843c1b099919f0d6d8d1f9f6a6b55cb"},"schema_version":"1.0"},"canonical_sha256":"71c83f4d81fda3e5e8ba1c7e2f04e323f4664bfbe5129bf01f6975b4aedef0c3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:17.672761Z","signature_b64":"sD/PsUYKzriWlS/v6t8lF5vjmasaCcipHZfKN7sZ9SHEe8MBwSrNzkwjMes4BBBK2+CdKsEr6bf5zzwgtsmSCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71c83f4d81fda3e5e8ba1c7e2f04e323f4664bfbe5129bf01f6975b4aedef0c3","last_reissued_at":"2026-05-18T00:00:17.672167Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:17.672167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.01474","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:00:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6x+FqhZpJbrv2EGFBSVoEfi5xgS9cBe3LQlW44AMZa4epJfvUSAbD9O/JVckitl0a+C+/piZtJnoK9sGW8eqAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T05:15:59.771117Z"},"content_sha256":"4653fc99c9cda36489f5dec79dd218efa858f5041f8704f243fd73985a4fea96","schema_version":"1.0","event_id":"sha256:4653fc99c9cda36489f5dec79dd218efa858f5041f8704f243fd73985a4fea96"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OHED6TMB7WR6L2F2DR7C6BHDEP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fast Face Image Synthesis with Minimal Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kevin W. Bowyer, Patrick J. Flynn, Sandipan Banerjee, Walter J. Scheirer","submitted_at":"2018-11-05T01:28:53Z","abstract_excerpt":"We propose an algorithm to generate realistic face images of both real and synthetic identities (people who do not exist) with different facial yaw, shape and resolution.The synthesized images can be used to augment datasets to train CNNs or as massive distractor sets for biometric verification experiments without any privacy concerns. Additionally, law enforcement can make use of this technique to train forensic experts to recognize faces. Our method samples face components from a pool of multiple face images of real identities to generate the synthetic texture. Then, a real 3D head model com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.01474","kind":"arxiv","version":3},"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":"2026-05-18T00:00:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nVB5YfGyfaHinFAe5PBsPi0A0vx0gW7DTjDgAhdbs1CVNep1pc3OKxbzxbTeIx8ANedWZMGhdlauHwv7bQT5Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T05:15:59.771722Z"},"content_sha256":"ed8bc97b2dcb3a287559ae924df7615e2c310d083e5f38ef0e402bc8f7c361f2","schema_version":"1.0","event_id":"sha256:ed8bc97b2dcb3a287559ae924df7615e2c310d083e5f38ef0e402bc8f7c361f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/bundle.json","state_url":"https://pith.science/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/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":"2026-06-01T05:15:59Z","links":{"resolver":"https://pith.science/pith/OHED6TMB7WR6L2F2DR7C6BHDEP","bundle":"https://pith.science/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/bundle.json","state":"https://pith.science/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OHED6TMB7WR6L2F2DR7C6BHDEP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OHED6TMB7WR6L2F2DR7C6BHDEP","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":"8117d186ab338acd041ccf8cef8d225b7843c1b099919f0d6d8d1f9f6a6b55cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-05T01:28:53Z","title_canon_sha256":"5171d3220b3872392e194ea5d998703b288dee942498961999ac5a8a84d2fe95"},"schema_version":"1.0","source":{"id":"1811.01474","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.01474","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"arxiv_version","alias_value":"1811.01474v3","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.01474","created_at":"2026-05-18T00:00:17Z"},{"alias_kind":"pith_short_12","alias_value":"OHED6TMB7WR6","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OHED6TMB7WR6L2F2","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OHED6TMB","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:ed8bc97b2dcb3a287559ae924df7615e2c310d083e5f38ef0e402bc8f7c361f2","target":"graph","created_at":"2026-05-18T00:00:17Z","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":"We propose an algorithm to generate realistic face images of both real and synthetic identities (people who do not exist) with different facial yaw, shape and resolution.The synthesized images can be used to augment datasets to train CNNs or as massive distractor sets for biometric verification experiments without any privacy concerns. Additionally, law enforcement can make use of this technique to train forensic experts to recognize faces. Our method samples face components from a pool of multiple face images of real identities to generate the synthetic texture. Then, a real 3D head model com","authors_text":"Kevin W. Bowyer, Patrick J. Flynn, Sandipan Banerjee, Walter J. Scheirer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-05T01:28:53Z","title":"Fast Face Image Synthesis with Minimal Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.01474","kind":"arxiv","version":3},"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":"sha256:4653fc99c9cda36489f5dec79dd218efa858f5041f8704f243fd73985a4fea96","target":"record","created_at":"2026-05-18T00:00:17Z","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":"8117d186ab338acd041ccf8cef8d225b7843c1b099919f0d6d8d1f9f6a6b55cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-05T01:28:53Z","title_canon_sha256":"5171d3220b3872392e194ea5d998703b288dee942498961999ac5a8a84d2fe95"},"schema_version":"1.0","source":{"id":"1811.01474","kind":"arxiv","version":3}},"canonical_sha256":"71c83f4d81fda3e5e8ba1c7e2f04e323f4664bfbe5129bf01f6975b4aedef0c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"71c83f4d81fda3e5e8ba1c7e2f04e323f4664bfbe5129bf01f6975b4aedef0c3","first_computed_at":"2026-05-18T00:00:17.672167Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:17.672167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sD/PsUYKzriWlS/v6t8lF5vjmasaCcipHZfKN7sZ9SHEe8MBwSrNzkwjMes4BBBK2+CdKsEr6bf5zzwgtsmSCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:17.672761Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.01474","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4653fc99c9cda36489f5dec79dd218efa858f5041f8704f243fd73985a4fea96","sha256:ed8bc97b2dcb3a287559ae924df7615e2c310d083e5f38ef0e402bc8f7c361f2"],"state_sha256":"42f0f53d7ee4605368327b28299d427561e2fbc0ac96280cb6fd3276eddf698d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XYrRJMhwpxB/Ywp2AdNT9hN/zhl9u8MPfptbXRtCLvS2Ubt1iqd3zLKeH2qFX1ic7oIow63JML3XXL/3GouQBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T05:15:59.774999Z","bundle_sha256":"a9a2ecbf21312faafdbef28ff804bf6dbe1aa5601216b0c9c81ccbfe66c3a5ac"}}