{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:5IALWHEYL2TH6S3EZZVZAELB3C","short_pith_number":"pith:5IALWHEY","canonical_record":{"source":{"id":"1712.00516","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-01T23:12:58Z","cross_cats_sorted":[],"title_canon_sha256":"e614369d95d989664c7a85c5bc7da0ca96138e9083dceb468780dccc3edf6c05","abstract_canon_sha256":"7f53312a98d64b84c5846351c1763404397c6cfd2880999f69357588d84d169d"},"schema_version":"1.0"},"canonical_sha256":"ea00bb1c985ea67f4b64ce6b901161d89547095adf7e0d26be0bc2fa4822587c","source":{"kind":"arxiv","id":"1712.00516","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00516","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00516v1","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00516","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"pith_short_12","alias_value":"5IALWHEYL2TH","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5IALWHEYL2TH6S3E","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5IALWHEY","created_at":"2026-05-18T12:31:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:5IALWHEYL2TH6S3EZZVZAELB3C","target":"record","payload":{"canonical_record":{"source":{"id":"1712.00516","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-01T23:12:58Z","cross_cats_sorted":[],"title_canon_sha256":"e614369d95d989664c7a85c5bc7da0ca96138e9083dceb468780dccc3edf6c05","abstract_canon_sha256":"7f53312a98d64b84c5846351c1763404397c6cfd2880999f69357588d84d169d"},"schema_version":"1.0"},"canonical_sha256":"ea00bb1c985ea67f4b64ce6b901161d89547095adf7e0d26be0bc2fa4822587c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:05.044170Z","signature_b64":"Qhf5VE7vhmBfaKckFQmmJOzIVkuFfW29/4Hz/6+5g7kyfl0yY9lNu5kDRiYW5TfZ4Gg/ui+SNvtnXukMWNh/CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea00bb1c985ea67f4b64ce6b901161d89547095adf7e0d26be0bc2fa4822587c","last_reissued_at":"2026-05-18T00:29:05.043412Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:05.043412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.00516","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":"2026-05-18T00:29:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UffNMygg76Zgm2DSm3rlgh8Yf/nG7bPn4UkrQX4WuCAhgaIkEkvmrq+7B7jN13ee6mAEja0Ncf9zffH5+bI2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:53:31.956546Z"},"content_sha256":"fcbcc46ed2ca9210c742ab0815b9339df3daf4fbe903740ac40d72884bd36333","schema_version":"1.0","event_id":"sha256:fcbcc46ed2ca9210c742ab0815b9339df3daf4fbe903740ac40d72884bd36333"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:5IALWHEYL2TH6S3EZZVZAELB3C","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Content GAN for Few-Shot Font Style Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Eli Shechtman, Matthew Fisher, Samaneh Azadi, Trevor Darrell, Vladimir Kim, Zhaowen Wang","submitted_at":"2017-12-01T23:12:58Z","abstract_excerpt":"In this work, we focus on the challenge of taking partial observations of highly-stylized text and generalizing the observations to generate unobserved glyphs in the ornamented typeface. To generate a set of multi-content images following a consistent style from very few examples, we propose an end-to-end stacked conditional GAN model considering content along channels and style along network layers. Our proposed network transfers the style of given glyphs to the contents of unseen ones, capturing highly stylized fonts found in the real-world such as those on movie posters or infographics. We "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00516","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":"2026-05-18T00:29:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hdCPgfHDcsW9jU8tVZcn9hfbvev+KPmEWlCjhjP5Y4MhMkvjRKzquxIhbm5cyyenS2l8DmtVCnRXbUKFJSQ9Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:53:31.956869Z"},"content_sha256":"065b177a4de01885ef76ec73837a5896b71406973a2e24161e3d73797872abdb","schema_version":"1.0","event_id":"sha256:065b177a4de01885ef76ec73837a5896b71406973a2e24161e3d73797872abdb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5IALWHEYL2TH6S3EZZVZAELB3C/bundle.json","state_url":"https://pith.science/pith/5IALWHEYL2TH6S3EZZVZAELB3C/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5IALWHEYL2TH6S3EZZVZAELB3C/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":"2026-06-02T07:53:31Z","links":{"resolver":"https://pith.science/pith/5IALWHEYL2TH6S3EZZVZAELB3C","bundle":"https://pith.science/pith/5IALWHEYL2TH6S3EZZVZAELB3C/bundle.json","state":"https://pith.science/pith/5IALWHEYL2TH6S3EZZVZAELB3C/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5IALWHEYL2TH6S3EZZVZAELB3C/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5IALWHEYL2TH6S3EZZVZAELB3C","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":"7f53312a98d64b84c5846351c1763404397c6cfd2880999f69357588d84d169d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-01T23:12:58Z","title_canon_sha256":"e614369d95d989664c7a85c5bc7da0ca96138e9083dceb468780dccc3edf6c05"},"schema_version":"1.0","source":{"id":"1712.00516","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00516","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00516v1","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00516","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"pith_short_12","alias_value":"5IALWHEYL2TH","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5IALWHEYL2TH6S3E","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5IALWHEY","created_at":"2026-05-18T12:31:00Z"}],"graph_snapshots":[{"event_id":"sha256:065b177a4de01885ef76ec73837a5896b71406973a2e24161e3d73797872abdb","target":"graph","created_at":"2026-05-18T00:29:05Z","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":"In this work, we focus on the challenge of taking partial observations of highly-stylized text and generalizing the observations to generate unobserved glyphs in the ornamented typeface. To generate a set of multi-content images following a consistent style from very few examples, we propose an end-to-end stacked conditional GAN model considering content along channels and style along network layers. Our proposed network transfers the style of given glyphs to the contents of unseen ones, capturing highly stylized fonts found in the real-world such as those on movie posters or infographics. We ","authors_text":"Eli Shechtman, Matthew Fisher, Samaneh Azadi, Trevor Darrell, Vladimir Kim, Zhaowen Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-01T23:12:58Z","title":"Multi-Content GAN for Few-Shot Font Style Transfer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00516","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:fcbcc46ed2ca9210c742ab0815b9339df3daf4fbe903740ac40d72884bd36333","target":"record","created_at":"2026-05-18T00:29:05Z","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":"7f53312a98d64b84c5846351c1763404397c6cfd2880999f69357588d84d169d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-01T23:12:58Z","title_canon_sha256":"e614369d95d989664c7a85c5bc7da0ca96138e9083dceb468780dccc3edf6c05"},"schema_version":"1.0","source":{"id":"1712.00516","kind":"arxiv","version":1}},"canonical_sha256":"ea00bb1c985ea67f4b64ce6b901161d89547095adf7e0d26be0bc2fa4822587c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ea00bb1c985ea67f4b64ce6b901161d89547095adf7e0d26be0bc2fa4822587c","first_computed_at":"2026-05-18T00:29:05.043412Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:05.043412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qhf5VE7vhmBfaKckFQmmJOzIVkuFfW29/4Hz/6+5g7kyfl0yY9lNu5kDRiYW5TfZ4Gg/ui+SNvtnXukMWNh/CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:05.044170Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.00516","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fcbcc46ed2ca9210c742ab0815b9339df3daf4fbe903740ac40d72884bd36333","sha256:065b177a4de01885ef76ec73837a5896b71406973a2e24161e3d73797872abdb"],"state_sha256":"140a1cefc523c8a6e07ab627486c7a4834c0e312f7ce4f5020e684c4147c9515"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ihaCyJ9eLS2WJcq7/6tN61qaCgnGJqfqZBI/JUIeif/F5TnkPK3YlJbbgEDhieSQ8Pqo85g5LWLxLnVQAdHBDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T07:53:31.959132Z","bundle_sha256":"b2281982a15f71a0b7b2bee64ba7bf73aa882eb049e0c0a333cf2f5e9ccce999"}}