176 lines
6.8 KiB
Markdown
176 lines
6.8 KiB
Markdown
# Dataset Zoo
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We provide several relevant datasets for training and evaluating the Joint Detection and Embedding (JDE) model.
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Annotations are provided in a unified format. If you want to use these datasets, please **follow their licenses**,
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and if you use these datasets in your research, please cite the original work (you can find the BibTeX in the bottom).
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## Data Format
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All the dataset has the following structure:
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```
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Caltech
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|——————images
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| └——————00001.jpg
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| |—————— ...
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| └——————0000N.jpg
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└——————labels_with_ids
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└——————00001.txt
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|—————— ...
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└——————0000N.txt
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```
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Every image corresponds to an annotation text. Given an image path,
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the annotation text path can be easily generated by replacing the string `images` with `labels_with_ids` and replacing `.jpg` with `.txt`.
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In the annotation text, each line is a bounding box and has the following format,
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```
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[class] [identity] [x_center] [y_center] [width] [height]
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```
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The field `[class]` should be `0`. Only single-class multi-object tracking is supported in this version.
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The field `[identity]` is an integer from `0` to `num_identities - 1`, or `-1` if this box has no identity annotation.
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***Note** that the values of `[x_center] [y_center] [width] [height]` are normalized by the width/height of the image, so they are float numbers ranging from 0 to 1.
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## Download
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### Caltech Pedestrian
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/1sYBXXvQaXZ8TuNwQxMcAgg)
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[[1]](https://pan.baidu.com/s/1lVO7YBzagex1xlzqPksaPw)
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[[2]](https://pan.baidu.com/s/1PZXxxy_lrswaqTVg0GuHWg)
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[[3]](https://pan.baidu.com/s/1M93NCo_E6naeYPpykmaNgA)
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[[4]](https://pan.baidu.com/s/1ZXCdPNXfwbxQ4xCbVu5Dtw)
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[[5]](https://pan.baidu.com/s/1kcZkh1tcEiBEJqnDtYuejg)
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[[6]](https://pan.baidu.com/s/1sDjhtgdFrzR60KKxSjNb2A)
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[[7]](https://pan.baidu.com/s/18Zvp_d33qj1pmutFDUbJyw)
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Google Drive: [[annotation]](https://drive.google.com/file/d/1h8vxl_6tgi9QVYoer9XcY9YwNB32TE5k/view?usp=sharing) ,
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please download all the `.tar` file from [this page](http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/datasets/USA/) and unzip the images under `Caltech/images`
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Original dataset webpage: [CaltechPedestrians](http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/)
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### CityPersons
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/1g24doGOdkKqmbgbJf03vsw)
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[[1]](https://pan.baidu.com/s/1mqDF9M5MdD3MGxSfe0ENsA)
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[[2]](https://pan.baidu.com/s/1Qrbh9lQUaEORCIlfI25wdA)
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[[3]](https://pan.baidu.com/s/1lw7shaffBgARDuk8mkkHhw)
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Google Drive:
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[[0]](https://drive.google.com/file/d/1DgLHqEkQUOj63mCrS_0UGFEM9BG8sIZs/view?usp=sharing)
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[[1]](https://drive.google.com/file/d/1BH9Xz59UImIGUdYwUR-cnP1g7Ton_LcZ/view?usp=sharing)
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[[2]](https://drive.google.com/file/d/1q_OltirP68YFvRWgYkBHLEFSUayjkKYE/view?usp=sharing)
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[[3]](https://drive.google.com/file/d/1VSL0SFoQxPXnIdBamOZJzHrHJ1N2gsTW/view?usp=sharing)
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Original dataset webpage: [Citypersons pedestrian detection dataset](https://bitbucket.org/shanshanzhang/citypersons)
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### CUHK-SYSU
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/1YFrlyB1WjcQmFW3Vt_sEaQ)
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Google Drive:
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[[0]](https://drive.google.com/file/d/1D7VL43kIV9uJrdSCYl53j89RE2K-IoQA/view?usp=sharing)
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Original dataset webpage: [CUHK-SYSU Person Search Dataset](http://www.ee.cuhk.edu.hk/~xgwang/PS/dataset.html)
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### PRW
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/1iqOVKO57dL53OI1KOmWeGQ)
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Google Drive:
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[[0]](https://drive.google.com/file/d/116_mIdjgB-WJXGe8RYJDWxlFnc_4sqS8/view?usp=sharing)
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Original dataset webpage: [Person Search in the Wild datset](http://www.liangzheng.com.cn/Project/project_prw.html)
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### ETHZ (overlapping videos with MOT-16 removed):
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/14EauGb2nLrcB3GRSlQ4K9Q)
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Google Drive:
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[[0]](https://drive.google.com/file/d/19QyGOCqn8K_rc9TXJ8UwLSxCx17e0GoY/view?usp=sharing)
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Original dataset webpage: [ETHZ pedestrian datset](https://data.vision.ee.ethz.ch/cvl/aess/dataset/)
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### MOT-17
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/1lHa6UagcosRBz-_Y308GvQ)
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Google Drive:
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[[0]](https://drive.google.com/file/d/1ET-6w12yHNo8DKevOVgK1dBlYs739e_3/view?usp=sharing)
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Original dataset webpage: [MOT-17](https://motchallenge.net/data/MOT17/)
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### MOT-16 (for evaluation )
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Baidu NetDisk:
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[[0]](https://pan.baidu.com/s/10pUuB32Hro-h-KUZv8duiw)
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Google Drive:
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[[0]](https://drive.google.com/file/d/1254q3ruzBzgn4LUejDVsCtT05SIEieQg/view?usp=sharing)
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Original dataset webpage: [MOT-16](https://motchallenge.net/data/MOT16/)
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# Citation
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Caltech:
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```
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@inproceedings{ dollarCVPR09peds,
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author = "P. Doll\'ar and C. Wojek and B. Schiele and P. Perona",
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title = "Pedestrian Detection: A Benchmark",
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booktitle = "CVPR",
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month = "June",
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year = "2009",
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city = "Miami",
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}
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```
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Citypersons:
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```
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@INPROCEEDINGS{Shanshan2017CVPR,
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Author = {Shanshan Zhang and Rodrigo Benenson and Bernt Schiele},
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Title = {CityPersons: A Diverse Dataset for Pedestrian Detection},
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Booktitle = {CVPR},
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Year = {2017}
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}
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@INPROCEEDINGS{Cordts2016Cityscapes,
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title={The Cityscapes Dataset for Semantic Urban Scene Understanding},
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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},
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booktitle={Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
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year={2016}
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}
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```
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CUHK-SYSU:
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```
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@inproceedings{xiaoli2017joint,
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title={Joint Detection and Identification Feature Learning for Person Search},
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author={Xiao, Tong and Li, Shuang and Wang, Bochao and Lin, Liang and Wang, Xiaogang},
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booktitle={CVPR},
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year={2017}
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}
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```
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PRW:
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```
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@inproceedings{zheng2017person,
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title={Person re-identification in the wild},
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author={Zheng, Liang and Zhang, Hengheng and Sun, Shaoyan and Chandraker, Manmohan and Yang, Yi and Tian, Qi},
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booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
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pages={1367--1376},
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year={2017}
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}
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```
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ETHZ:
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```
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@InProceedings{eth_biwi_00534,
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author = {A. Ess and B. Leibe and K. Schindler and and L. van Gool},
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title = {A Mobile Vision System for Robust Multi-Person Tracking},
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booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR'08)},
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year = {2008},
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month = {June},
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publisher = {IEEE Press},
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keywords = {}
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}
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```
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MOT-16&17:
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```
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@article{milan2016mot16,
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title={MOT16: A benchmark for multi-object tracking},
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author={Milan, Anton and Leal-Taix{\'e}, Laura and Reid, Ian and Roth, Stefan and Schindler, Konrad},
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journal={arXiv preprint arXiv:1603.00831},
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year={2016}
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}
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```
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