Computer Science > Information Retrieval
[Submitted on 8 Apr 2022 (v1), last revised 18 Apr 2023 (this version, v4)]
Title:Contrastive language and vision learning of general fashion concepts
View PDFAbstract: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.
Submission history
From: Jacopo Tagliabue [view email][v1] Fri, 8 Apr 2022 10:01:39 UTC (1,170 KB)
[v2] Mon, 11 Apr 2022 16:41:29 UTC (1,170 KB)
[v3] Thu, 2 Mar 2023 23:13:14 UTC (1,170 KB)
[v4] Tue, 18 Apr 2023 23:32:12 UTC (1,170 KB)
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