{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:O7SL6HV5CQKXKUEWCVE7OQBJMH","short_pith_number":"pith:O7SL6HV5","schema_version":"1.0","canonical_sha256":"77e4bf1ebd14157550961549f7402961e09ef8c3ba739ef887c9489f94914a70","source":{"kind":"arxiv","id":"1711.07027","version":3},"attestation_state":"computed","paper":{"title":"Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guoliang Kang, Jianbin Jiao, Liang Zheng, Qixiang Ye, Weijian Deng, Yi Yang","submitted_at":"2017-11-19T15:05:17Z","abstract_excerpt":"Person re-identification (re-ID) models trained on one domain often fail to generalize well to another. In our attempt, we present a \"learning via translation\" framework. In the baseline, we translate the labeled images from source to target domain in an unsupervised manner. We then train re-ID models with the translated images by supervised methods. Yet, being an essential part of this framework, unsupervised image-image translation suffers from the information loss of source-domain labels during translation.\n  Our motivation is two-fold. First, for each image, the discriminative cues contain"},"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":"1711.07027","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2017-11-19T15:05:17Z","cross_cats_sorted":[],"title_canon_sha256":"d94513d259f08485eca1425c95fca6d6d510fa6a973b080cc4d4af4957c20932","abstract_canon_sha256":"b52d1d934ec0e18099d0d44a399505155ddb78bfb5a2b398e9008ebcbaf0f4aa"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:58.653464Z","signature_b64":"knCh5HHtLtY2gD+l9VamRTx5uspPMEUnf+rwZeg7HlrpEfQb8dIFNenSSrg8N8AJ7K4evARrUNPyQZDGEilRCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"77e4bf1ebd14157550961549f7402961e09ef8c3ba739ef887c9489f94914a70","last_reissued_at":"2026-05-18T00:15:58.652199Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:58.652199Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guoliang Kang, Jianbin Jiao, Liang Zheng, Qixiang Ye, Weijian Deng, Yi Yang","submitted_at":"2017-11-19T15:05:17Z","abstract_excerpt":"Person re-identification (re-ID) models trained on one domain often fail to generalize well to another. In our attempt, we present a \"learning via translation\" framework. In the baseline, we translate the labeled images from source to target domain in an unsupervised manner. We then train re-ID models with the translated images by supervised methods. Yet, being an essential part of this framework, unsupervised image-image translation suffers from the information loss of source-domain labels during translation.\n  Our motivation is two-fold. First, for each image, the discriminative cues contain"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.07027","kind":"arxiv","version":3},"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":"1711.07027","created_at":"2026-05-18T00:15:58.652310+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.07027v3","created_at":"2026-05-18T00:15:58.652310+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.07027","created_at":"2026-05-18T00:15:58.652310+00:00"},{"alias_kind":"pith_short_12","alias_value":"O7SL6HV5CQKX","created_at":"2026-05-18T12:31:34.259226+00:00"},{"alias_kind":"pith_short_16","alias_value":"O7SL6HV5CQKXKUEW","created_at":"2026-05-18T12:31:34.259226+00:00"},{"alias_kind":"pith_short_8","alias_value":"O7SL6HV5","created_at":"2026-05-18T12:31:34.259226+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/O7SL6HV5CQKXKUEWCVE7OQBJMH","json":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH.json","graph_json":"https://pith.science/api/pith-number/O7SL6HV5CQKXKUEWCVE7OQBJMH/graph.json","events_json":"https://pith.science/api/pith-number/O7SL6HV5CQKXKUEWCVE7OQBJMH/events.json","paper":"https://pith.science/paper/O7SL6HV5"},"agent_actions":{"view_html":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH","download_json":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH.json","view_paper":"https://pith.science/paper/O7SL6HV5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.07027&json=true","fetch_graph":"https://pith.science/api/pith-number/O7SL6HV5CQKXKUEWCVE7OQBJMH/graph.json","fetch_events":"https://pith.science/api/pith-number/O7SL6HV5CQKXKUEWCVE7OQBJMH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH/action/storage_attestation","attest_author":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH/action/author_attestation","sign_citation":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH/action/citation_signature","submit_replication":"https://pith.science/pith/O7SL6HV5CQKXKUEWCVE7OQBJMH/action/replication_record"}},"created_at":"2026-05-18T00:15:58.652310+00:00","updated_at":"2026-05-18T00:15:58.652310+00:00"}