About the Dataset

JTA (Joint Track Auto) is a huge dataset for pedestrian pose estimation and tracking in urban scenarios created by exploiting the highly photorealistic video game Grand Theft Auto V developed by Rockstar North. We collected a set of 512 full-HD videos (256 for training and 256 for testing), 30 seconds long, recorded at 30 fps.

Details

• ~500K frames
• ~10M body poses
• 3D annotation
• Occlusion annotation

Download the Dataset

You can download JTA here. By downloading the dataset you agree on the following statement:

"I declare that I will use the JTA Dataset for research and educational purposes only, since I am aware that commercial use is prohibited. I also undertake to purchase a copy of Grand Theft Auto V."

You can find the GitHub repository here.

Download the Mods

You can find the mods here.

Acknowledgments

The work is supported by the Italian MIUR, Ministry of Education, Universities and Research, under the project COSMOS PRIN 2015 programme 201548C5NT. We also gratefully acknowledge the support of Panasonic Silicon Valley Lab and Facebook AI Research with the donation of the GPUs used for this research. We finally thank Marco Gianelli and Emanuele Frascaroli for developing part of the mod used to acquire JTA dataset.

License

JTA-Dataset is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Citation

We believe in open research and we are happy if you find this data useful. If you use it, please cite our work.

 @inproceedings{fabbri2018learning,
   title     = {Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World},
   author    = {Fabbri, Matteo and Lanzi, Fabio and Calderara, Simone and Palazzi, Andrea and 
                Vezzani, Roberto and Cucchiara, Rita},
   booktitle = {European Conference on Computer Vision (ECCV)},
   year      = {2018}
 }