{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:RNFYHGYSFJXNLWGRB6OBM5E7EN","short_pith_number":"pith:RNFYHGYS","schema_version":"1.0","canonical_sha256":"8b4b839b122a6ed5d8d10f9c16749f23655076819647cf0f0994a6dd85a009a9","source":{"kind":"arxiv","id":"2008.04200","version":1},"attestation_state":"computed","paper":{"title":"Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CV","authors_text":"Bruno Lepri, Deng Cai, Huayang Li, Marco De Nadai, Nicu Sebe, Xavier Alameda-Pineda, Yahui Liu","submitted_at":"2020-08-10T15:40:05Z","abstract_excerpt":"Manipulating visual attributes of images through human-written text is a very challenging task. On the one hand, models have to learn the manipulation without the ground truth of the desired output. On the other hand, models have to deal with the inherent ambiguity of natural language. Previous research usually requires either the user to describe all the characteristics of the desired image or to use richly-annotated image captioning datasets. In this work, we propose a novel unsupervised approach, based on image-to-image translation, that alters the attributes of a given image through a comm"},"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":"2008.04200","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-10T15:40:05Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"1100261c2a1568171cccfbd484e7f2e3eb0328b760966ac3986440e574a18914","abstract_canon_sha256":"291981f703299aebe4a47e8bdc6ca9d78bae0fddbb9c0d34be15bf4e10a12c74"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:26:00.852539Z","signature_b64":"j0mRs6MbPDTaELaCt0odo6t6owE1KFzexEGWaq3/X9pZYvkzZbNvAXAoHxywydennLHDktBCsN6EOhnnCmuIBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b4b839b122a6ed5d8d10f9c16749f23655076819647cf0f0994a6dd85a009a9","last_reissued_at":"2026-07-05T01:26:00.852025Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:26:00.852025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CV","authors_text":"Bruno Lepri, Deng Cai, Huayang Li, Marco De Nadai, Nicu Sebe, Xavier Alameda-Pineda, Yahui Liu","submitted_at":"2020-08-10T15:40:05Z","abstract_excerpt":"Manipulating visual attributes of images through human-written text is a very challenging task. On the one hand, models have to learn the manipulation without the ground truth of the desired output. On the other hand, models have to deal with the inherent ambiguity of natural language. Previous research usually requires either the user to describe all the characteristics of the desired image or to use richly-annotated image captioning datasets. In this work, we propose a novel unsupervised approach, based on image-to-image translation, that alters the attributes of a given image through a comm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.04200","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/2008.04200/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":"2008.04200","created_at":"2026-07-05T01:26:00.852090+00:00"},{"alias_kind":"arxiv_version","alias_value":"2008.04200v1","created_at":"2026-07-05T01:26:00.852090+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.04200","created_at":"2026-07-05T01:26:00.852090+00:00"},{"alias_kind":"pith_short_12","alias_value":"RNFYHGYSFJXN","created_at":"2026-07-05T01:26:00.852090+00:00"},{"alias_kind":"pith_short_16","alias_value":"RNFYHGYSFJXNLWGR","created_at":"2026-07-05T01:26:00.852090+00:00"},{"alias_kind":"pith_short_8","alias_value":"RNFYHGYS","created_at":"2026-07-05T01:26:00.852090+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/RNFYHGYSFJXNLWGRB6OBM5E7EN","json":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN.json","graph_json":"https://pith.science/api/pith-number/RNFYHGYSFJXNLWGRB6OBM5E7EN/graph.json","events_json":"https://pith.science/api/pith-number/RNFYHGYSFJXNLWGRB6OBM5E7EN/events.json","paper":"https://pith.science/paper/RNFYHGYS"},"agent_actions":{"view_html":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN","download_json":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN.json","view_paper":"https://pith.science/paper/RNFYHGYS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2008.04200&json=true","fetch_graph":"https://pith.science/api/pith-number/RNFYHGYSFJXNLWGRB6OBM5E7EN/graph.json","fetch_events":"https://pith.science/api/pith-number/RNFYHGYSFJXNLWGRB6OBM5E7EN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN/action/storage_attestation","attest_author":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN/action/author_attestation","sign_citation":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN/action/citation_signature","submit_replication":"https://pith.science/pith/RNFYHGYSFJXNLWGRB6OBM5E7EN/action/replication_record"}},"created_at":"2026-07-05T01:26:00.852090+00:00","updated_at":"2026-07-05T01:26:00.852090+00:00"}