{"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/learning-the-latent-look-unsupervised","title":"Learning the Latent \"Look\": Unsupervised Discovery of a Style-Coherent Embedding from Fashion Images","arxiv_id":"1707.03376","date":"2017-07-11","proceeding":"ICCV 2017 10","authors":["Wei-Lin Hsiao","Kristen Grauman"],"abstract":"What defines a visual style? Fashion styles emerge organically from how\npeople assemble outfits of clothing, making them difficult to pin down with a\ncomputational model. Low-level visual similarity can be too specific to detect\nstylistically similar images, while manually crafted style categories can be\ntoo abstract to capture subtle style differences. We propose an unsupervised\napproach to learn a style-coherent representation. Our method leverages\nprobabilistic polylingual topic models based on visual attributes to discover a\nset of latent style factors. Given a collection of unlabeled fashion images,\nour approach mines for the latent styles, then summarizes outfits by how they\nmix those styles. Our approach can organize galleries of outfits by style\nwithout requiring any style labels. Experiments on over 100K images demonstrate\nits promise for retrieving, mixing, and summarizing fashion images by their\nstyle.","url_abs":"http://arxiv.org/abs/1707.03376v2","url_pdf":"http://arxiv.org/pdf/1707.03376v2.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":"learning-the-latent-look-unsupervised","repo_url":"https://github.com/arodri202/dl-final-project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"topic-models","task_name":"Topic Models"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1707.03376","atlas_url":"https://app.syntology.ai/?focus=1707.03376","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}