{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:N67PT5J7TNJVKBMSDNZJQXPJJP","short_pith_number":"pith:N67PT5J7","canonical_record":{"source":{"id":"1809.08488","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-22T21:10:06Z","cross_cats_sorted":[],"title_canon_sha256":"3d4f86b0a88f4878b1365214f1ce86640d06c26077ba837aa97ba97f560fad4d","abstract_canon_sha256":"21f953338cd6ae3aad1ba63759f764a3a662db7f2971ee50ef71902ab20a78b2"},"schema_version":"1.0"},"canonical_sha256":"6fbef9f53f9b535505921b72985de94be61509680de7e9b16bab6ffd54375d2a","source":{"kind":"arxiv","id":"1809.08488","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.08488","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"arxiv_version","alias_value":"1809.08488v1","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.08488","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"pith_short_12","alias_value":"N67PT5J7TNJV","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"N67PT5J7TNJVKBMS","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"N67PT5J7","created_at":"2026-05-18T12:32:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:N67PT5J7TNJVKBMSDNZJQXPJJP","target":"record","payload":{"canonical_record":{"source":{"id":"1809.08488","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-22T21:10:06Z","cross_cats_sorted":[],"title_canon_sha256":"3d4f86b0a88f4878b1365214f1ce86640d06c26077ba837aa97ba97f560fad4d","abstract_canon_sha256":"21f953338cd6ae3aad1ba63759f764a3a662db7f2971ee50ef71902ab20a78b2"},"schema_version":"1.0"},"canonical_sha256":"6fbef9f53f9b535505921b72985de94be61509680de7e9b16bab6ffd54375d2a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:04.302576Z","signature_b64":"ysSI0uSoJ4V3NLivTeYHn8RLdcGJWn8qnfOT2/lAg1naebnTP0GmC3GRTzJaJF0JiUD4L255ngEWaa+semlDDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6fbef9f53f9b535505921b72985de94be61509680de7e9b16bab6ffd54375d2a","last_reissued_at":"2026-05-18T00:05:04.301982Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:04.301982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.08488","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":"2026-05-18T00:05:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JDk2ZesUSoy8AIYRJvNQt0Y9s9Sw17nyHPnFwy3QdzyQmm2HgQapbwdIMM+2Y7J32cybqTYs8V32aWfyFEsCCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T14:51:18.012180Z"},"content_sha256":"3d2c9742963a29b96dc32646733fb64b53f779d8546bea5c592c73395b701456","schema_version":"1.0","event_id":"sha256:3d2c9742963a29b96dc32646733fb64b53f779d8546bea5c592c73395b701456"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:N67PT5J7TNJVKBMSDNZJQXPJJP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Parametric Synthesis of Text on Stylized Backgrounds using PGGANs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abhinav Kumar, Mayank Gupta, Sriganesh Madhvanath","submitted_at":"2018-09-22T21:10:06Z","abstract_excerpt":"We describe a novel method of generating high-resolution real-world images of text where the style and textual content of the images are described parametrically. Our method combines text to image retrieval techniques with progressive growing of Generative Adversarial Networks (PGGANs) to achieve conditional generation of photo-realistic images that reflect specific styles, as well as artifacts seen in real-world images. We demonstrate our method in the context of automotive license plates. We assess the impact of varying the number of training images of each style on the fidelity of the gener"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.08488","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":"2026-05-18T00:05:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X7jbM2rL7vN4e5WzCb96qeyTz/1Z/VeZnHovDI/r5Bn+9TE4xkse4skPsq6/k+XlaTilvfTWoX/wJ3fuPGnPDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T14:51:18.012594Z"},"content_sha256":"54156f6058febb730258d854759a7fbb3ff47d770ca421201f1d763ccff45680","schema_version":"1.0","event_id":"sha256:54156f6058febb730258d854759a7fbb3ff47d770ca421201f1d763ccff45680"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/bundle.json","state_url":"https://pith.science/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/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":"2026-05-29T14:51:18Z","links":{"resolver":"https://pith.science/pith/N67PT5J7TNJVKBMSDNZJQXPJJP","bundle":"https://pith.science/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/bundle.json","state":"https://pith.science/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N67PT5J7TNJVKBMSDNZJQXPJJP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:N67PT5J7TNJVKBMSDNZJQXPJJP","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":"21f953338cd6ae3aad1ba63759f764a3a662db7f2971ee50ef71902ab20a78b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-22T21:10:06Z","title_canon_sha256":"3d4f86b0a88f4878b1365214f1ce86640d06c26077ba837aa97ba97f560fad4d"},"schema_version":"1.0","source":{"id":"1809.08488","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.08488","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"arxiv_version","alias_value":"1809.08488v1","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.08488","created_at":"2026-05-18T00:05:04Z"},{"alias_kind":"pith_short_12","alias_value":"N67PT5J7TNJV","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"N67PT5J7TNJVKBMS","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"N67PT5J7","created_at":"2026-05-18T12:32:40Z"}],"graph_snapshots":[{"event_id":"sha256:54156f6058febb730258d854759a7fbb3ff47d770ca421201f1d763ccff45680","target":"graph","created_at":"2026-05-18T00:05:04Z","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 describe a novel method of generating high-resolution real-world images of text where the style and textual content of the images are described parametrically. Our method combines text to image retrieval techniques with progressive growing of Generative Adversarial Networks (PGGANs) to achieve conditional generation of photo-realistic images that reflect specific styles, as well as artifacts seen in real-world images. We demonstrate our method in the context of automotive license plates. We assess the impact of varying the number of training images of each style on the fidelity of the gener","authors_text":"Abhinav Kumar, Mayank Gupta, Sriganesh Madhvanath","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-22T21:10:06Z","title":"Parametric Synthesis of Text on Stylized Backgrounds using PGGANs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.08488","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":"sha256:3d2c9742963a29b96dc32646733fb64b53f779d8546bea5c592c73395b701456","target":"record","created_at":"2026-05-18T00:05:04Z","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":"21f953338cd6ae3aad1ba63759f764a3a662db7f2971ee50ef71902ab20a78b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-22T21:10:06Z","title_canon_sha256":"3d4f86b0a88f4878b1365214f1ce86640d06c26077ba837aa97ba97f560fad4d"},"schema_version":"1.0","source":{"id":"1809.08488","kind":"arxiv","version":1}},"canonical_sha256":"6fbef9f53f9b535505921b72985de94be61509680de7e9b16bab6ffd54375d2a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6fbef9f53f9b535505921b72985de94be61509680de7e9b16bab6ffd54375d2a","first_computed_at":"2026-05-18T00:05:04.301982Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:04.301982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ysSI0uSoJ4V3NLivTeYHn8RLdcGJWn8qnfOT2/lAg1naebnTP0GmC3GRTzJaJF0JiUD4L255ngEWaa+semlDDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:04.302576Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.08488","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d2c9742963a29b96dc32646733fb64b53f779d8546bea5c592c73395b701456","sha256:54156f6058febb730258d854759a7fbb3ff47d770ca421201f1d763ccff45680"],"state_sha256":"e1431e9e67f0bf0c23b9e16372451d11caa2ffd4e7a3e2df2f57c8119cf86d6d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"16vpQNmD7qnLxbgwGBfs5Vw7YNoM8uVpYqXYVPAUbLiXp7U6rZPBGIxSrPYGzggSyW57nbKKtfW/V09C8H+TDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T14:51:18.014972Z","bundle_sha256":"0ef40a8fc6643628853eef6429ed48ce1561ca201cc56d04b6c365d6cb24dfcd"}}