Skip to content

Latest commit

 

History

History
177 lines (150 loc) · 6.92 KB

DATASET_ZOO.md

File metadata and controls

177 lines (150 loc) · 6.92 KB
Raw

Dataset Zoo

We provide several relevant datasets for training and evaluating the Joint Detection and Embedding (JDE) model. Annotations are provided in a unified format. If you want to use these datasets, please follow their licenses, and if you use any of these datasets in your research, please cite the original work (you can find the BibTeX in the bottom).

Data Format

All the datasets have the following structure:

Caltech
   |——————images
   |        └——————00001.jpg
   |        |—————— ...
   |        └——————0000N.jpg
   └——————labels_with_ids
            └——————00001.txt
            |—————— ...
            └——————0000N.txt

Every image has a corresponding annotation text. Given an image path, the annotation text path can be generated by replacing the string images with labels_with_ids and replacing .jpg with .txt.

In the annotation text, each line is describing a bounding box and has the following format:

[class] [identity] [x_center] [y_center] [width] [height]

The field [class] should be 0. Only single-class multi-object tracking is supported in this version.

The field [identity] is an integer from 0 to num_identities - 1, or -1 if this box has no identity annotation.

*Note that the values of [x_center] [y_center] [width] [height] are normalized by the width/height of the image, so they are floating point numbers ranging from 0 to 1.

Download

Caltech Pedestrian

Baidu NetDisk: [0] [1] [2] [3] [4] [5] [6] [7]

Google Drive: [annotations] , please download all the images .tar files from this page and unzip the images under Caltech/images

You may need this tool to convert the original data format to jpeg images. Original dataset webpage: CaltechPedestrians

CityPersons

Baidu NetDisk: [0] [1] [2] [3]

Google Drive: [0] [1] [2] [3]

Original dataset webpage: Citypersons pedestrian detection dataset

CUHK-SYSU

Baidu NetDisk: [0]

Google Drive: [0]

Original dataset webpage: CUHK-SYSU Person Search Dataset

PRW

Baidu NetDisk: [0]

Google Drive: [0]

Original dataset webpage: Person Search in the Wild datset

ETHZ (overlapping videos with MOT-16 removed):

Baidu NetDisk: [0]

Google Drive: [0]

Original dataset webpage: ETHZ pedestrian datset

MOT-17

Baidu NetDisk: [0]

Google Drive: [0]

Original dataset webpage: MOT-17

MOT-16 (for evaluation )

Baidu NetDisk: [0]

Google Drive: [0]

Original dataset webpage: MOT-16

Citation

Caltech:

@inproceedings{ dollarCVPR09peds,
       author = "P. Doll\'ar and C. Wojek and B. Schiele and  P. Perona",
       title = "Pedestrian Detection: A Benchmark",
       booktitle = "CVPR",
       month = "June",
       year = "2009",
       city = "Miami",
}

Citypersons:

@INPROCEEDINGS{Shanshan2017CVPR,
  Author = {Shanshan Zhang and Rodrigo Benenson and Bernt Schiele},
  Title = {CityPersons: A Diverse Dataset for Pedestrian Detection},
  Booktitle = {CVPR},
  Year = {2017}
 }

@INPROCEEDINGS{Cordts2016Cityscapes,
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)},
year={2016}
}

CUHK-SYSU:

@inproceedings{xiaoli2017joint,
  title={Joint Detection and Identification Feature Learning for Person Search},
  author={Xiao, Tong and Li, Shuang and Wang, Bochao and Lin, Liang and Wang, Xiaogang},
  booktitle={CVPR},
  year={2017}
}

PRW:

@inproceedings{zheng2017person,
  title={Person re-identification in the wild},
  author={Zheng, Liang and Zhang, Hengheng and Sun, Shaoyan and Chandraker, Manmohan and Yang, Yi and Tian, Qi},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1367--1376},
  year={2017}
}

ETHZ:

@InProceedings{eth_biwi_00534,
author = {A. Ess and B. Leibe and K. Schindler and and L. van Gool},
title = {A Mobile Vision System for Robust Multi-Person Tracking},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR'08)},
year = {2008},
month = {June},
publisher = {IEEE Press},
keywords = {}
}

MOT-16&17:

@article{milan2016mot16,
  title={MOT16: A benchmark for multi-object tracking},
  author={Milan, Anton and Leal-Taix{\'e}, Laura and Reid, Ian and Roth, Stefan and Schindler, Konrad},
  journal={arXiv preprint arXiv:1603.00831},
  year={2016}
}