{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QN7QXCYLXTQKWBVGXVK6IB3WI3","short_pith_number":"pith:QN7QXCYL","schema_version":"1.0","canonical_sha256":"837f0b8b0bbce0ab06a6bd55e4077646ec542bb4ab1851e65caf9a73b05f2eaa","source":{"kind":"arxiv","id":"1901.01569","version":2},"attestation_state":"computed","paper":{"title":"Segmentation Guided Image-to-Image Translation with Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Songyao Jiang, Yun Fu, Zhiqiang Tao","submitted_at":"2019-01-06T16:36:15Z","abstract_excerpt":"Recently image-to-image translation has received increasing attention, which aims to map images in one domain to another specific one. Existing methods mainly solve this task via a deep generative model, and focus on exploring the relationship between different domains. However, these methods neglect to utilize higher-level and instance-specific information to guide the training process, leading to a great deal of unrealistic generated images of low quality. Existing methods also lack of spatial controllability during translation. To address these challenge, we propose a novel Segmentation Gui"},"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":"1901.01569","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-06T16:36:15Z","cross_cats_sorted":[],"title_canon_sha256":"94065d20737de36235350cab86bab1d985ba4ef8f2f643bba5857dcd963778e4","abstract_canon_sha256":"622d9866ef6f9f685e5767c8c94179b74dc76e6a375574dfb3fffc3662b5cce1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:42.316646Z","signature_b64":"Q5ZHMyo4zUOBz4eC+k7eEi6VVP4omro2HrM8tCW8duyX950WJsq1XIcoWGhQkTDp9wSWXoXkr4RDtl6jCW62CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"837f0b8b0bbce0ab06a6bd55e4077646ec542bb4ab1851e65caf9a73b05f2eaa","last_reissued_at":"2026-05-17T23:55:42.315722Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:42.315722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Segmentation Guided Image-to-Image Translation with Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Songyao Jiang, Yun Fu, Zhiqiang Tao","submitted_at":"2019-01-06T16:36:15Z","abstract_excerpt":"Recently image-to-image translation has received increasing attention, which aims to map images in one domain to another specific one. Existing methods mainly solve this task via a deep generative model, and focus on exploring the relationship between different domains. However, these methods neglect to utilize higher-level and instance-specific information to guide the training process, leading to a great deal of unrealistic generated images of low quality. Existing methods also lack of spatial controllability during translation. To address these challenge, we propose a novel Segmentation Gui"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01569","kind":"arxiv","version":2},"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":"1901.01569","created_at":"2026-05-17T23:55:42.315896+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.01569v2","created_at":"2026-05-17T23:55:42.315896+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01569","created_at":"2026-05-17T23:55:42.315896+00:00"},{"alias_kind":"pith_short_12","alias_value":"QN7QXCYLXTQK","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_16","alias_value":"QN7QXCYLXTQKWBVG","created_at":"2026-05-18T12:33:27.125529+00:00"},{"alias_kind":"pith_short_8","alias_value":"QN7QXCYL","created_at":"2026-05-18T12:33:27.125529+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/QN7QXCYLXTQKWBVGXVK6IB3WI3","json":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3.json","graph_json":"https://pith.science/api/pith-number/QN7QXCYLXTQKWBVGXVK6IB3WI3/graph.json","events_json":"https://pith.science/api/pith-number/QN7QXCYLXTQKWBVGXVK6IB3WI3/events.json","paper":"https://pith.science/paper/QN7QXCYL"},"agent_actions":{"view_html":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3","download_json":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3.json","view_paper":"https://pith.science/paper/QN7QXCYL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.01569&json=true","fetch_graph":"https://pith.science/api/pith-number/QN7QXCYLXTQKWBVGXVK6IB3WI3/graph.json","fetch_events":"https://pith.science/api/pith-number/QN7QXCYLXTQKWBVGXVK6IB3WI3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3/action/storage_attestation","attest_author":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3/action/author_attestation","sign_citation":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3/action/citation_signature","submit_replication":"https://pith.science/pith/QN7QXCYLXTQKWBVGXVK6IB3WI3/action/replication_record"}},"created_at":"2026-05-17T23:55:42.315896+00:00","updated_at":"2026-05-17T23:55:42.315896+00:00"}