In-shop Clothes Retrieval Benchmark evaluates the performance of in-shop Clothes Retrievel. 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

  • Pair Annotations

  • Bounding Box Annotations

  • Type & Pose Annotations


  • Train/Val/Test Partitions

Evaluation Results

Coming soon.


 author = {Ziwei Liu, Ping Luo, Shi Qiu, Xiaogang Wang, and Xiaoou Tang},
 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.