{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:LGQYO7AWIK22ELKO5QNDTQBCXU","short_pith_number":"pith:LGQYO7AW","schema_version":"1.0","canonical_sha256":"59a1877c1642b5a22d4eec1a39c022bd391b450eb2421ba8ad755a33fda64270","source":{"kind":"arxiv","id":"2211.06198","version":1},"attestation_state":"computed","paper":{"title":"StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Jinshan Zeng, Mingwen Wang, Qi Chen, Yefei Wang, Yuan Yao, Yunxin Liu","submitted_at":"2022-11-11T13:39:26Z","abstract_excerpt":"The generation of Chinese fonts has a wide range of applications. The currently predominated methods are mainly based on deep generative models, especially the generative adversarial networks (GANs). However, existing GAN-based models usually suffer from the well-known mode collapse problem. When mode collapse happens, the kind of GAN-based models will be failure to yield the correct fonts. To address this issue, we introduce a one-bit stroke encoding and a few-shot semi-supervised scheme (i.e., using a few paired data as semi-supervised information) to explore the local and global structure i"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2211.06198","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-11T13:39:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f3197188d44a364766775126dbff2ceaa470e92bab38d8cf3135d494d3aa7754","abstract_canon_sha256":"c52cd01d981194b976492f165c88b2fe41aef9f91b7a00955b5067cb0a807ea3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:18.214471Z","signature_b64":"X1munbT5wJGJpbKU96MeixTtUWaX4mXLho5hN51FRsUuIJM6h1v/k1BgrqGmQnqkLvojykHjB0trM1tIHJq2CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59a1877c1642b5a22d4eec1a39c022bd391b450eb2421ba8ad755a33fda64270","last_reissued_at":"2026-07-05T05:15:18.214065Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:18.214065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Jinshan Zeng, Mingwen Wang, Qi Chen, Yefei Wang, Yuan Yao, Yunxin Liu","submitted_at":"2022-11-11T13:39:26Z","abstract_excerpt":"The generation of Chinese fonts has a wide range of applications. The currently predominated methods are mainly based on deep generative models, especially the generative adversarial networks (GANs). However, existing GAN-based models usually suffer from the well-known mode collapse problem. When mode collapse happens, the kind of GAN-based models will be failure to yield the correct fonts. To address this issue, we introduce a one-bit stroke encoding and a few-shot semi-supervised scheme (i.e., using a few paired data as semi-supervised information) to explore the local and global structure i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06198","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2211.06198/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2211.06198","created_at":"2026-07-05T05:15:18.214117+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.06198v1","created_at":"2026-07-05T05:15:18.214117+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06198","created_at":"2026-07-05T05:15:18.214117+00:00"},{"alias_kind":"pith_short_12","alias_value":"LGQYO7AWIK22","created_at":"2026-07-05T05:15:18.214117+00:00"},{"alias_kind":"pith_short_16","alias_value":"LGQYO7AWIK22ELKO","created_at":"2026-07-05T05:15:18.214117+00:00"},{"alias_kind":"pith_short_8","alias_value":"LGQYO7AW","created_at":"2026-07-05T05:15:18.214117+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU","json":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU.json","graph_json":"https://pith.science/api/pith-number/LGQYO7AWIK22ELKO5QNDTQBCXU/graph.json","events_json":"https://pith.science/api/pith-number/LGQYO7AWIK22ELKO5QNDTQBCXU/events.json","paper":"https://pith.science/paper/LGQYO7AW"},"agent_actions":{"view_html":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU","download_json":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU.json","view_paper":"https://pith.science/paper/LGQYO7AW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.06198&json=true","fetch_graph":"https://pith.science/api/pith-number/LGQYO7AWIK22ELKO5QNDTQBCXU/graph.json","fetch_events":"https://pith.science/api/pith-number/LGQYO7AWIK22ELKO5QNDTQBCXU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU/action/storage_attestation","attest_author":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU/action/author_attestation","sign_citation":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU/action/citation_signature","submit_replication":"https://pith.science/pith/LGQYO7AWIK22ELKO5QNDTQBCXU/action/replication_record"}},"created_at":"2026-07-05T05:15:18.214117+00:00","updated_at":"2026-07-05T05:15:18.214117+00:00"}