{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rasa-relation-and-sensitivity-aware","title":"RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search","arxiv_id":"2305.13653","date":"2023-05-23","proceeding":null,"authors":["Yang Bai","Min Cao","Daming Gao","Ziqiang Cao","Chen Chen","Zhenfeng Fan","Liqiang Nie","Min Zhang"],"abstract":"Text-based person search aims to retrieve the specified person images given a textual description. The key to tackling such a challenging task is to learn powerful multi-modal representations. Towards this, we propose a Relation and Sensitivity aware representation learning method (RaSa), including two novel tasks: Relation-Aware learning (RA) and Sensitivity-Aware learning (SA). For one thing, existing methods cluster representations of all positive pairs without distinction and overlook the noise problem caused by the weak positive pairs where the text and the paired image have noise correspondences, thus leading to overfitting learning. RA offsets the overfitting risk by introducing a novel positive relation detection task (i.e., learning to distinguish strong and weak positive pairs). For another thing, learning invariant representation under data augmentation (i.e., being insensitive to some transformations) is a general practice for improving representation's robustness in existing methods. Beyond that, we encourage the representation to perceive the sensitive transformation by SA (i.e., learning to detect the replaced words), thus promoting the representation's robustness. Experiments demonstrate that RaSa outperforms existing state-of-the-art methods by 6.94%, 4.45% and 15.35% in terms of Rank@1 on CUHK-PEDES, ICFG-PEDES and RSTPReid datasets, respectively. Code is available at: https://github.com/Flame-Chasers/RaSa.","url_abs":"https://arxiv.org/abs/2305.13653v1","url_pdf":"https://arxiv.org/pdf/2305.13653v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"rasa-relation-and-sensitivity-aware","repo_url":"https://github.com/flame-chasers/rasa","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"person-search","task_name":"Person Search"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"sensitivity","task_name":"Sensitivity"},{"task_slug":"nlp-based-person-retrival","task_name":"Text based Person Retrieval"},{"task_slug":"text-based-person-search","task_name":"Text based Person Search"}],"methods":[{"method_slug":"albef","method_name":"ALBEF"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/nlp-based-person-retrival-on-cuhk-pedes","task":"Text based Person Retrieval","dataset":"CUHK-PEDES","model":"RaSa","rank_in_archive_order":3,"of":21,"metrics":{"R@1":"76.51","R@10":"94.25","R@5":"90.29","mAP":"69.38"},"uses_additional_data":false},{"leaderboard":"/sota/text-based-person-retrieval-on-icfg-pedes","task":"Text based Person Retrieval","dataset":"ICFG-PEDES","model":"RaSa","rank_in_archive_order":5,"of":12,"metrics":{"R@1":"65.28","R@10":"85.12","R@5":"80.4","mAP":"41.29"},"uses_additional_data":false},{"leaderboard":"/sota/text-based-person-retrieval-on-rstpreid-1","task":"Text based Person Retrieval","dataset":"RSTPReid","model":"RaSa","rank_in_archive_order":3,"of":9,"metrics":{"R@1":"66.90","R@10":"91.35","R@5":"86.50","mAP":"52.31"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2305.13653","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.13653"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/flame-chasers/rasa","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/Flame-Chasers/RaSa","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_draft_wrong":3,"unverified":4},"by_repo_kind":{"official":{"samples":7,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"cf9ffa02a42184af","entry":"whitespace_tokenize","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"models/tokenization_bert.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/models/tokenization_bert.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":2,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"cf9ffa02a42184af"}},{"code_sha256_prefix":"c6ec173f19f5c34d","entry":"interpolate_pos_embed","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"models/vit.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/models/vit.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c6ec173f19f5c34d"}},{"code_sha256_prefix":"e7fbc7a74a3457c7","entry":"load_vocab","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"models/tokenization_bert.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/models/tokenization_bert.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e7fbc7a74a3457c7"}},{"code_sha256_prefix":"73cecca9f3575f09","entry":"concat_all_gather","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"models/model_person_search.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/models/model_person_search.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"73cecca9f3575f09"}},{"code_sha256_prefix":"c6527ef1dd35e7f1","entry":"itm_eval","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"Retrieval.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/Retrieval.py","link_basis":"plan_row","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c6527ef1dd35e7f1"}},{"code_sha256_prefix":"26be70dca3249c0b","entry":"load_tf_weights_in_bert","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"models/xbert.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/models/xbert.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"26be70dca3249c0b"}},{"code_sha256_prefix":"8a57c3e7d1cf36c7","entry":"pre_caption","repo":"Flame-Chasers/RaSa","repo_kind":"official","path":"dataset/utils.py","file_url":"https://github.com/Flame-Chasers/RaSa/blob/HEAD/dataset/utils.py","link_basis":"plan_row","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8a57c3e7d1cf36c7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}