{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:2ENMAFVRI2Z2T4OXYCR6UXG2VJ","short_pith_number":"pith:2ENMAFVR","canonical_record":{"source":{"id":"1807.01493","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T09:21:19Z","cross_cats_sorted":[],"title_canon_sha256":"df1b09516ed91cde4ea660978b594207566b996a37198ac6eca9b4fbdcb602ae","abstract_canon_sha256":"1bb1362794e74b7b672b4b6311221d8dabab6251cb91a8873b6d81fc5d914f69"},"schema_version":"1.0"},"canonical_sha256":"d11ac016b146b3a9f1d7c0a3ea5cdaaa7d2b3d53a14bba49e0658a12014d4f85","source":{"kind":"arxiv","id":"1807.01493","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.01493","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"arxiv_version","alias_value":"1807.01493v1","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.01493","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"pith_short_12","alias_value":"2ENMAFVRI2Z2","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"2ENMAFVRI2Z2T4OX","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"2ENMAFVR","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:2ENMAFVRI2Z2T4OXYCR6UXG2VJ","target":"record","payload":{"canonical_record":{"source":{"id":"1807.01493","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T09:21:19Z","cross_cats_sorted":[],"title_canon_sha256":"df1b09516ed91cde4ea660978b594207566b996a37198ac6eca9b4fbdcb602ae","abstract_canon_sha256":"1bb1362794e74b7b672b4b6311221d8dabab6251cb91a8873b6d81fc5d914f69"},"schema_version":"1.0"},"canonical_sha256":"d11ac016b146b3a9f1d7c0a3ea5cdaaa7d2b3d53a14bba49e0658a12014d4f85","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:29.593543Z","signature_b64":"jWmKdsNW7PYD11SZWomcDaVfiX0hxagD29Sgms/tYfReMBX2O5poxuekwU2TGrMwlTIkcM9X+JfWurd3sQvwBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d11ac016b146b3a9f1d7c0a3ea5cdaaa7d2b3d53a14bba49e0658a12014d4f85","last_reissued_at":"2026-05-18T00:11:29.593086Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:29.593086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.01493","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":"2026-05-18T00:11:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x+fFNaGDM/G9dvbNeU6Rg3R2qAEAaKDEaLHS1c9pppv1wYP6/WAE3yY9LnfGQp1wh/vXCeYnphGrRck3lK1RDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T09:53:40.750473Z"},"content_sha256":"6216841d5897f7eddf3dfbcb075079482fa50724bda22d8abbc0b999561fd400","schema_version":"1.0","event_id":"sha256:6216841d5897f7eddf3dfbcb075079482fa50724bda22d8abbc0b999561fd400"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:2ENMAFVRI2Z2T4OXYCR6UXG2VJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Uncorrelated Feature Encoding for Faster Image Style Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hyun-Chul Choi, Jongju Shin, Minseong Kim, Myung-Cheol Roh","submitted_at":"2018-07-04T09:21:19Z","abstract_excerpt":"Recent fast style transfer methods use a pre-trained convolutional neural network as a feature encoder and a perceptual loss network. Although the pre-trained network is used to generate responses of receptive fields effective for representing style and content of image, it is not optimized for image style transfer but rather for image classification. Furthermore, it also requires a time-consuming and correlation-considering feature alignment process for image style transfer because of its inter-channel correlation. In this paper, we propose an end-to-end learning method which optimizes an enc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.01493","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":"2026-05-18T00:11:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+gFkga3rGjPRnJmEacVdyJUffSZjlG5953F3baf5pFHyGWmLQcTHhkt/diH9gOdpOQ54zt6zzIlCBqwjKCjTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T09:53:40.750823Z"},"content_sha256":"8f00350f36f6491d8584ed2229d923b158f404ebf5728b8a8f1f8fd2756b07f4","schema_version":"1.0","event_id":"sha256:8f00350f36f6491d8584ed2229d923b158f404ebf5728b8a8f1f8fd2756b07f4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/bundle.json","state_url":"https://pith.science/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/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":"2026-06-20T09:53:40Z","links":{"resolver":"https://pith.science/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ","bundle":"https://pith.science/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/bundle.json","state":"https://pith.science/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2ENMAFVRI2Z2T4OXYCR6UXG2VJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:2ENMAFVRI2Z2T4OXYCR6UXG2VJ","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":"1bb1362794e74b7b672b4b6311221d8dabab6251cb91a8873b6d81fc5d914f69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T09:21:19Z","title_canon_sha256":"df1b09516ed91cde4ea660978b594207566b996a37198ac6eca9b4fbdcb602ae"},"schema_version":"1.0","source":{"id":"1807.01493","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.01493","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"arxiv_version","alias_value":"1807.01493v1","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.01493","created_at":"2026-05-18T00:11:29Z"},{"alias_kind":"pith_short_12","alias_value":"2ENMAFVRI2Z2","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"2ENMAFVRI2Z2T4OX","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"2ENMAFVR","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:8f00350f36f6491d8584ed2229d923b158f404ebf5728b8a8f1f8fd2756b07f4","target":"graph","created_at":"2026-05-18T00:11:29Z","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":"Recent fast style transfer methods use a pre-trained convolutional neural network as a feature encoder and a perceptual loss network. Although the pre-trained network is used to generate responses of receptive fields effective for representing style and content of image, it is not optimized for image style transfer but rather for image classification. Furthermore, it also requires a time-consuming and correlation-considering feature alignment process for image style transfer because of its inter-channel correlation. In this paper, we propose an end-to-end learning method which optimizes an enc","authors_text":"Hyun-Chul Choi, Jongju Shin, Minseong Kim, Myung-Cheol Roh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T09:21:19Z","title":"Uncorrelated Feature Encoding for Faster Image Style Transfer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.01493","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":"sha256:6216841d5897f7eddf3dfbcb075079482fa50724bda22d8abbc0b999561fd400","target":"record","created_at":"2026-05-18T00:11:29Z","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":"1bb1362794e74b7b672b4b6311221d8dabab6251cb91a8873b6d81fc5d914f69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-04T09:21:19Z","title_canon_sha256":"df1b09516ed91cde4ea660978b594207566b996a37198ac6eca9b4fbdcb602ae"},"schema_version":"1.0","source":{"id":"1807.01493","kind":"arxiv","version":1}},"canonical_sha256":"d11ac016b146b3a9f1d7c0a3ea5cdaaa7d2b3d53a14bba49e0658a12014d4f85","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d11ac016b146b3a9f1d7c0a3ea5cdaaa7d2b3d53a14bba49e0658a12014d4f85","first_computed_at":"2026-05-18T00:11:29.593086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:11:29.593086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jWmKdsNW7PYD11SZWomcDaVfiX0hxagD29Sgms/tYfReMBX2O5poxuekwU2TGrMwlTIkcM9X+JfWurd3sQvwBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:11:29.593543Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.01493","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6216841d5897f7eddf3dfbcb075079482fa50724bda22d8abbc0b999561fd400","sha256:8f00350f36f6491d8584ed2229d923b158f404ebf5728b8a8f1f8fd2756b07f4"],"state_sha256":"899c994718ca286050d2117116c34efaff053cc92784fe6f7c941636ff849db1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KhIwwz9vxrYatL3cFIs2oQLcMjIK19AYMzKbo44GlNq+owwWogHAjbrsjbb+sDEqJKpc3OGK40dZWfa/beLmAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T09:53:40.753174Z","bundle_sha256":"825ee03e61237ba1734e232e3b4a377456ddb53c40eb48092bb74d7e1719a11d"}}