This repo provides bounding box annotations, python evaluation code, and a benchmark for CityPersons, which is a subset of the Cityscapes dataset. Please download the images from the Cityscapes website!

Welcome to join the competition by submitting your results on the test set!


Method MR (Reasonable) MR (Reasonable_small) MR (Reasonable_occ=heavy) MR (All)
HBA-RCNN 11.06% 14.77% 43.61% 39.54%
OR-CNN 11.32% 14.19% 51.43% 40.19%
Repultion Loss 11.48% 15.67% 52.59% 39.17%
Adapted FasterRCNN 12.97% 37.24% 50.47% 43.86%

Please refer to the instructions on submitting results for evaluation.

What Do We Have?

Annotation Example



If you use this data and code, please kindly cite the following papers:


  Author = {Shanshan Zhang and Rodrigo Benenson and Bernt Schiele},

  Title = {CityPersons: A Diverse Dataset for Pedestrian Detection},

  Booktitle = {CVPR},

  Year = {2017}


title={The Cityscapes Dataset for Semantic Urban Scene Understanding},

author={Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt},

booktitle={Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},


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