论文标题
对比的语言和视觉学习一般时尚概念
Contrastive language and vision learning of general fashion concepts
论文作者
论文摘要
在线购物的稳定上升与日益复杂的ML和NLP模型的发展息息相关。虽然大多数用例都是作为专门监督的学习问题而施放的，但我们认为从业者将从更可转移的产品表示中受益匪浅。在这项工作中，我们基于对比型学习的最新发展，以培训FashionClip，这是一种类似于时装行业的剪辑模型。我们展示了其检索，分类和接地的功能，并将我们的模型和代码发布给社区。
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.
