{"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/relatable-clothing-detecting-visual","title":"Relatable Clothing: Detecting Visual Relationships between People and Clothing","arxiv_id":"2007.10283","date":"2020-07-20","proceeding":null,"authors":["Thomas Truong","Svetlana Yanushkevich"],"abstract":"Detecting visual relationships between people and clothing in an image has been a relatively unexplored problem in the field of computer vision and biometrics. The lack readily available public dataset for ``worn'' and ``unworn'' classification has slowed the development of solutions for this problem. We present the release of the Relatable Clothing Dataset which contains 35287 person-clothing pairs and segmentation masks for the development of ``worn'' and ``unworn'' classification models. Additionally, we propose a novel soft attention unit for performing ``worn'' and ``unworn'' classification using deep neural networks. The proposed soft attention models have an accuracy of upward $98.55\\% \\pm 0.35\\%$ on the Relatable Clothing Dataset and demonstrate high generalizable, allowing us to classify unseen articles of clothing such as high visibility vests as ``worn'' or ``unworn''.","url_abs":"https://arxiv.org/abs/2007.10283v1","url_pdf":"https://arxiv.org/pdf/2007.10283v1.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":"relatable-clothing-detecting-visual","repo_url":"https://github.com/th-truong/relatable_clothing","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}