{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:4GNYN7WQ4UDWGEZKN4C2H4K4TB","short_pith_number":"pith:4GNYN7WQ","canonical_record":{"source":{"id":"1705.04058","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-11T08:08:44Z","cross_cats_sorted":["cs.NE","eess.IV","stat.ML"],"title_canon_sha256":"c9c6615dc9d9cf2ddb2ce0564f113dcc6d22ccbd4f46081760757db7fb4b3857","abstract_canon_sha256":"e53f60b3ce8b925740e4b1a2fbaedbb3f96c592115250e8e49786618c63ee6c5"},"schema_version":"1.0"},"canonical_sha256":"e19b86fed0e50763132a6f05a3f15c9853202edfc8a669b09538c925d5c25bd8","source":{"kind":"arxiv","id":"1705.04058","version":7},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.04058","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"arxiv_version","alias_value":"1705.04058v7","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.04058","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"pith_short_12","alias_value":"4GNYN7WQ4UDW","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"4GNYN7WQ4UDWGEZK","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"4GNYN7WQ","created_at":"2026-05-18T12:30:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:4GNYN7WQ4UDWGEZKN4C2H4K4TB","target":"record","payload":{"canonical_record":{"source":{"id":"1705.04058","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-11T08:08:44Z","cross_cats_sorted":["cs.NE","eess.IV","stat.ML"],"title_canon_sha256":"c9c6615dc9d9cf2ddb2ce0564f113dcc6d22ccbd4f46081760757db7fb4b3857","abstract_canon_sha256":"e53f60b3ce8b925740e4b1a2fbaedbb3f96c592115250e8e49786618c63ee6c5"},"schema_version":"1.0"},"canonical_sha256":"e19b86fed0e50763132a6f05a3f15c9853202edfc8a669b09538c925d5c25bd8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:02.170534Z","signature_b64":"WRYBFwD0OMFsFikwJ7SatD3CP0fLgZBDnz/2LS/gX3YZWJI9iypjfGJ+kONlS26ts58/iTBT3ZlUsysKGB5NCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e19b86fed0e50763132a6f05a3f15c9853202edfc8a669b09538c925d5c25bd8","last_reissued_at":"2026-05-18T00:02:02.169988Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:02.169988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.04058","source_version":7,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:02:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L5deKnUuoR2FDdFo+TlHzmwZvuXkB6vDqCrEWOVvUfmy9R7BUmDTJseMkxnKSeZc1lHhzMdbTdqcIcn7PEPwAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T19:02:35.884729Z"},"content_sha256":"32a60b221cedd84f1efd312b83aedc0a7b4c3922f7a9a17d4caa71bea69a53a1","schema_version":"1.0","event_id":"sha256:32a60b221cedd84f1efd312b83aedc0a7b4c3922f7a9a17d4caa71bea69a53a1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:4GNYN7WQ4UDWGEZKN4C2H4K4TB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Style Transfer: A Review","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE","eess.IV","stat.ML"],"primary_cat":"cs.CV","authors_text":"Jingwen Ye, Mingli Song, Yezhou Yang, Yizhou Yu, Yongcheng Jing, Zunlei Feng","submitted_at":"2017-05-11T08:08:44Z","abstract_excerpt":"The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST). Since then, NST has become a trending topic both in academic literature and industrial applications. It is receiving increasing attention and a variety of approaches are proposed to either improve or extend the original NST algorithm. In this paper, we aim to provide a comprehensive overview of the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.04058","kind":"arxiv","version":7},"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":"2026-05-18T00:02:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GmNGNqVRfyZwQ+0hrXpxLBwlxo3i2pkOh9SLM8wBnpJez/G+U9V4id4C10uApsco2CAyvkvF47fCqJZo4dP5Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T19:02:35.885070Z"},"content_sha256":"45ea828d4c154b90e038fcc2f1be83bca9af55c49b2cdccbe0cb95e3c5086df3","schema_version":"1.0","event_id":"sha256:45ea828d4c154b90e038fcc2f1be83bca9af55c49b2cdccbe0cb95e3c5086df3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/bundle.json","state_url":"https://pith.science/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/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":"2026-07-01T19:02:35Z","links":{"resolver":"https://pith.science/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB","bundle":"https://pith.science/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/bundle.json","state":"https://pith.science/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4GNYN7WQ4UDWGEZKN4C2H4K4TB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:4GNYN7WQ4UDWGEZKN4C2H4K4TB","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":"e53f60b3ce8b925740e4b1a2fbaedbb3f96c592115250e8e49786618c63ee6c5","cross_cats_sorted":["cs.NE","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-11T08:08:44Z","title_canon_sha256":"c9c6615dc9d9cf2ddb2ce0564f113dcc6d22ccbd4f46081760757db7fb4b3857"},"schema_version":"1.0","source":{"id":"1705.04058","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.04058","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"arxiv_version","alias_value":"1705.04058v7","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.04058","created_at":"2026-05-18T00:02:02Z"},{"alias_kind":"pith_short_12","alias_value":"4GNYN7WQ4UDW","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"4GNYN7WQ4UDWGEZK","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"4GNYN7WQ","created_at":"2026-05-18T12:30:58Z"}],"graph_snapshots":[{"event_id":"sha256:45ea828d4c154b90e038fcc2f1be83bca9af55c49b2cdccbe0cb95e3c5086df3","target":"graph","created_at":"2026-05-18T00:02:02Z","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":"The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST). Since then, NST has become a trending topic both in academic literature and industrial applications. It is receiving increasing attention and a variety of approaches are proposed to either improve or extend the original NST algorithm. In this paper, we aim to provide a comprehensive overview of the ","authors_text":"Jingwen Ye, Mingli Song, Yezhou Yang, Yizhou Yu, Yongcheng Jing, Zunlei Feng","cross_cats":["cs.NE","eess.IV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-11T08:08:44Z","title":"Neural Style Transfer: A Review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.04058","kind":"arxiv","version":7},"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":"sha256:32a60b221cedd84f1efd312b83aedc0a7b4c3922f7a9a17d4caa71bea69a53a1","target":"record","created_at":"2026-05-18T00:02:02Z","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":"e53f60b3ce8b925740e4b1a2fbaedbb3f96c592115250e8e49786618c63ee6c5","cross_cats_sorted":["cs.NE","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-11T08:08:44Z","title_canon_sha256":"c9c6615dc9d9cf2ddb2ce0564f113dcc6d22ccbd4f46081760757db7fb4b3857"},"schema_version":"1.0","source":{"id":"1705.04058","kind":"arxiv","version":7}},"canonical_sha256":"e19b86fed0e50763132a6f05a3f15c9853202edfc8a669b09538c925d5c25bd8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e19b86fed0e50763132a6f05a3f15c9853202edfc8a669b09538c925d5c25bd8","first_computed_at":"2026-05-18T00:02:02.169988Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:02.169988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WRYBFwD0OMFsFikwJ7SatD3CP0fLgZBDnz/2LS/gX3YZWJI9iypjfGJ+kONlS26ts58/iTBT3ZlUsysKGB5NCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:02.170534Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.04058","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32a60b221cedd84f1efd312b83aedc0a7b4c3922f7a9a17d4caa71bea69a53a1","sha256:45ea828d4c154b90e038fcc2f1be83bca9af55c49b2cdccbe0cb95e3c5086df3"],"state_sha256":"90bf5280401bf1b7f535c3f333afd1d3b619b724d15083c56ff90241bdc2acf2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ciLXS7Y6JS3rLn6V0wBJe1KnyjdV5p9KlHcf5Gz31m8PUeXaTysDMVV1t0UJwZs1QuEOPll9j2Br7s/VXa8JBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T19:02:35.886980Z","bundle_sha256":"49b45f0963bd9670284a2481ffd24aad47567475a8e0776425d1e6f5aecbc079"}}