articleJun 1, 2016Closed access

DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

Chinese University of Hong Kong · Shenzhen Institutes of Advanced Technology · +1 more institution

Indexed incrossref

Abstract

Recent advances in clothes recognition have been driven by the construction of clothes datasets. Existing datasets are limited in the amount of annotations and are difficult to cope with the various challenges in real-world applications. In this work, we introduce DeepFashion1, a large-scale clothes dataset with comprehensive annotations. It contains over 800,000 images, which are richly annotated with massive attributes, clothing landmarks, and correspondence of images taken under different scenarios including store, street snapshot, and consumer. Such rich annotations enable the development of powerful algorithms in clothes recognition and facilitating future researches. To demonstrate the advantages of…

No related works found for this paper.