We contribute DeepFashion database, a large-scale clothes database, which has several appealing properties:
1、First, DeepFashion contains over 800,000 diverse fashion images ranging from well-posed shop images to unconstrained consumer photos, constituting the largest visual fashion analysis database.
2、Second, DeepFashion is annotated with rich information of clothing items. Each image in this dataset is labeled with 50 categories, 1,000 descriptive attributes, bounding box and clothing landmarks.
3、Third, DeepFashion contains over 300,000 cross-pose/cross-domain image pairs.
4、Four benchmarks are developed using the DeepFashion database, including Attribute Prediction, Consumer-to-shop Clothes Retrieval, In-shop Clothes Retrieval, and Landmark Detection. The data and annotations of these benchmarks can be also employed as the training and test sets for the following computer vision tasks, such as Clothes Detection, Clothes Recognition, and Image Retrieval.
Please read Download Instructions below to access the dataset.
1、The DeepFashion is available for non-commercial research purposes only.2、All images of the DeepFashion are obtained from the Internet which are not property of MMLAB, The Chinese University of Hong Kong. The MMLAB is not responsible for the content nor the meaning of these images.
3、You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
4、You agree not to further copy, publish or distribute any portion of the DeepFashion. Except, for internal use at a single site within the same organization it is allowed to make copies of the dataset.
5、The MMLAB reserves the right to terminate your access to the DeepFashion at any time.
1、Some image data are encrypted to prevent unauthorized access. Please download the DeepFashion dataset Release Agreement.
2、Read it carefully, complete and sign it appropriately. This is an example.
3、Please send the completed form to Ziwei Liu (firstname.lastname@example.org) and cc to Ping Luo (pluo(at)ie.cuhk.edu.hk) using institutional email address. The email Subject Title is "DeepFashion Agreement". We will verify your request and contact you with the passwords to unzip the image data.