{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:62ZESXMGSSPXYXECDIEG4IJTIP","short_pith_number":"pith:62ZESXMG","schema_version":"1.0","canonical_sha256":"f6b2495d86949f7c5c821a086e213343d40560d37d09b944aefeb40265d74cc9","source":{"kind":"arxiv","id":"1901.10895","version":1},"attestation_state":"computed","paper":{"title":"Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Bing Zheng, Haiyong Zheng, Ping Lin, Yang Wu, Zhibin Yu, Ziqiang Zheng","submitted_at":"2019-01-24T07:14:07Z","abstract_excerpt":"Current approaches have made great progress on image-to-image translation tasks benefiting from the success of image synthesis methods especially generative adversarial networks (GANs). However, existing methods are limited to handling translation tasks between two species while keeping the content matching on the semantic level. A more challenging task would be the translation among more than two species. To explore this new area, we propose a simple yet effective structure of a multi-branch discriminator for enhancing an arbitrary generative adversarial architecture (GAN), named GAN-MBD. It "},"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":"1901.10895","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2019-01-24T07:14:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f3710e15be674761b3338756e23db0e320c36b6293f41a9db51c82e94edcc45e","abstract_canon_sha256":"584f8b243b377d3ee19117c3366768289bb2815f7e1e2e60382e7e2215ed335b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:05.789407Z","signature_b64":"w84XVUtunWNHqf49WSnKEPxSt6/IOy8E9pPWK4m9cdZKS07xYFns1PYXtizpVyeAj1jhv2LynV9PDkGkuckeAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6b2495d86949f7c5c821a086e213343d40560d37d09b944aefeb40265d74cc9","last_reissued_at":"2026-05-17T23:55:05.788914Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:05.788914Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Bing Zheng, Haiyong Zheng, Ping Lin, Yang Wu, Zhibin Yu, Ziqiang Zheng","submitted_at":"2019-01-24T07:14:07Z","abstract_excerpt":"Current approaches have made great progress on image-to-image translation tasks benefiting from the success of image synthesis methods especially generative adversarial networks (GANs). However, existing methods are limited to handling translation tasks between two species while keeping the content matching on the semantic level. A more challenging task would be the translation among more than two species. To explore this new area, we propose a simple yet effective structure of a multi-branch discriminator for enhancing an arbitrary generative adversarial architecture (GAN), named GAN-MBD. It "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.10895","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1901.10895","created_at":"2026-05-17T23:55:05.789001+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.10895v1","created_at":"2026-05-17T23:55:05.789001+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.10895","created_at":"2026-05-17T23:55:05.789001+00:00"},{"alias_kind":"pith_short_12","alias_value":"62ZESXMGSSPX","created_at":"2026-05-18T12:33:10.108867+00:00"},{"alias_kind":"pith_short_16","alias_value":"62ZESXMGSSPXYXEC","created_at":"2026-05-18T12:33:10.108867+00:00"},{"alias_kind":"pith_short_8","alias_value":"62ZESXMG","created_at":"2026-05-18T12:33:10.108867+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/62ZESXMGSSPXYXECDIEG4IJTIP","json":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP.json","graph_json":"https://pith.science/api/pith-number/62ZESXMGSSPXYXECDIEG4IJTIP/graph.json","events_json":"https://pith.science/api/pith-number/62ZESXMGSSPXYXECDIEG4IJTIP/events.json","paper":"https://pith.science/paper/62ZESXMG"},"agent_actions":{"view_html":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP","download_json":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP.json","view_paper":"https://pith.science/paper/62ZESXMG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.10895&json=true","fetch_graph":"https://pith.science/api/pith-number/62ZESXMGSSPXYXECDIEG4IJTIP/graph.json","fetch_events":"https://pith.science/api/pith-number/62ZESXMGSSPXYXECDIEG4IJTIP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP/action/storage_attestation","attest_author":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP/action/author_attestation","sign_citation":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP/action/citation_signature","submit_replication":"https://pith.science/pith/62ZESXMGSSPXYXECDIEG4IJTIP/action/replication_record"}},"created_at":"2026-05-17T23:55:05.789001+00:00","updated_at":"2026-05-17T23:55:05.789001+00:00"}