{"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/fashionclip-connecting-language-and-images","title":"Contrastive language and vision learning of general fashion concepts","arxiv_id":"2204.03972","date":"2022-04-08","proceeding":"Scientific Reports 2022 11","authors":["Patrick John Chia","Giuseppe Attanasio","Federico Bianchi","Silvia Terragni","Ana Rita Magalhães","Diogo Goncalves","Ciro Greco","Jacopo Tagliabue"],"abstract":"The steady rise of online shopping goes hand in hand with the development of increasingly complex ML and NLP models. While most use cases are cast as specialized supervised learning problems, we argue that practitioners would greatly benefit from more transferable representations of products. In this work, we build on recent developments in contrastive learning to train FashionCLIP, a CLIP-like model for the fashion industry. We showcase its capabilities for retrieval, classification and grounding, and release our model and code to the community.","url_abs":"https://arxiv.org/abs/2204.03972v4","url_pdf":"https://arxiv.org/pdf/2204.03972v4.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":"fashionclip-connecting-language-and-images","repo_url":"https://github.com/patrickjohncyh/fashion-clip","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"contrastive-learning","task_name":"Contrastive Learning"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[{"method_slug":"contrastive-learning","method_name":"Contrastive Learning"},{"method_slug":"fashionclip","method_name":"FashionCLIP"}],"datasets_introduced":[],"methods_introduced":[{"slug":"fashionclip","name":"FashionCLIP","full_name":"FashionCLIP"}],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2204.03972","atlas_url":"https://app.syntology.ai/?focus=2204.03972","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.03972"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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. 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