In-shop Clothes Retrieval Benchmark evaluates the performance of in-shop Clothes Retrieval. This is a large subset of DeepFashion, containing large pose and scale variations. It also has large diversities, large quantities, and rich annotations, including

  • 7,982 number of clothing items;

  • 52,712 number of in-shop clothes images, and ~200,000 cross-pose/scale pairs;

  • Each image is annotated by bounding box, clothing type and pose type.


  • In-shop Clothes Images

  • High-Res Images

  • Identity & Pair Annotations

  • BBox & Landmark Annotations

  • Attribute Annotations

  • Parsing Mask Annotations

  • Dense Pose Annotations

  • Train/Val/Test Partitions


 author = {Liu, Ziwei and Luo, Ping and Qiu, Shi and Wang, Xiaogang and Tang, Xiaoou},
 title = {DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations},
 booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
 month = {June},
 year = {2016}


Please contact Ziwei Liu for questions about the dataset.