{"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/buy-me-that-look-an-approach-for-recommending","title":"Buy Me That Look: An Approach for Recommending Similar Fashion Products","arxiv_id":"2008.11638","date":"2020-08-26","proceeding":null,"authors":["Abhinav Ravi","Sandeep Repakula","Ujjal Kr Dutta","Maulik Parmar"],"abstract":"Have you ever looked at an Instagram model, or a model in a fashion e-commerce web-page, and thought \\textit{\"Wish I could get a list of fashion items similar to the ones worn by the model!\"}. This is what we address in this paper, where we propose a novel computer vision based technique called \\textbf{ShopLook} to address the challenging problem of recommending similar fashion products. The proposed method has been evaluated at Myntra (www.myntra.com), a leading online fashion e-commerce platform. In particular, given a user query and the corresponding Product Display Page (PDP) against the query, the goal of our method is to recommend similar fashion products corresponding to the entire set of fashion articles worn by a model in the PDP full-shot image (the one showing the entire model from head to toe). The novelty and strength of our method lies in its capability to recommend similar articles for all the fashion items worn by the model, in addition to the primary article corresponding to the query. This is not only important to promote cross-sells for boosting revenue, but also for improving customer experience and engagement. In addition, our approach is also capable of recommending similar products for User Generated Content (UGC), eg., fashion article images uploaded by users. Formally, our proposed method consists of the following components (in the same order): i) Human keypoint detection, ii) Pose classification, iii) Article localisation and object detection, along with active learning feedback, and iv) Triplet network based image embedding model.","url_abs":"https://arxiv.org/abs/2008.11638v2","url_pdf":"https://arxiv.org/pdf/2008.11638v2.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":"buy-me-that-look-an-approach-for-recommending","repo_url":"https://github.com/Mohammad-Asad-110/Fashion-Recommendation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"active-learning","task_name":"Active Learning"},{"task_slug":"articles","task_name":"Articles"},{"task_slug":"keypoint-detection","task_name":"Keypoint Detection"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":null,"task_name":"Triplet"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}