{"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/a-strong-baseline-for-fashion-retrieval-with","title":"A Strong Baseline for Fashion Retrieval with Person Re-Identification Models","arxiv_id":"2003.04094","date":"2020-03-09","proceeding":null,"authors":["Mikolaj Wieczorek","Andrzej Michalowski","Anna Wroblewska","Jacek Dabrowski"],"abstract":"Fashion retrieval is the challenging task of finding an exact match for fashion items contained within an image. Difficulties arise from the fine-grained nature of clothing items, very large intra-class and inter-class variance. Additionally, query and source images for the task usually come from different domains - street photos and catalogue photos respectively. Due to these differences, a significant gap in quality, lighting, contrast, background clutter and item presentation exists between domains. As a result, fashion retrieval is an active field of research both in academia and the industry. Inspired by recent advancements in Person Re-Identification research, we adapt leading ReID models to be used in fashion retrieval tasks. We introduce a simple baseline model for fashion retrieval, significantly outperforming previous state-of-the-art results despite a much simpler architecture. We conduct in-depth experiments on Street2Shop and DeepFashion datasets and validate our results. Finally, we propose a cross-domain (cross-dataset) evaluation method to test the robustness of fashion retrieval models.","url_abs":"https://arxiv.org/abs/2003.04094v1","url_pdf":"https://arxiv.org/pdf/2003.04094v1.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":"a-strong-baseline-for-fashion-retrieval-with","repo_url":"https://github.com/mikwieczorek/centroids-reid","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-retrieval","task_name":"Image Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-retrieval-on-deepfashion-consumer-to","task":"Image Retrieval","dataset":"DeepFashion - Consumer-to-shop","model":"RST Model (ResNet50-IBN-A, 320x320)","rank_in_archive_order":2,"of":4,"metrics":{"Rank-1":"37.8","Rank-10":"71.1","Rank-20":"77.2","Rank-50":"84.1","mAP":"43.0"},"uses_additional_data":false},{"leaderboard":"/sota/image-retrieval-on-exact-street2shop","task":"Image Retrieval","dataset":"Exact Street2Shop","model":"RST Model (ResNet50-IBN-A, 320x320)","rank_in_archive_order":2,"of":3,"metrics":{"Rank-1":"53.7","Rank-10":"69.8","Rank-20":"73.6","mAP":"46.8"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2003.04094","atlas_url":"https://app.syntology.ai/?focus=2003.04094","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}