Attributes in Crowd Dataset


About the Dataset

AiC (Attributes in Crowd) is a novel synthetic dataset for people attribute recognition in presence of strong occlusions created by exploiting the highly photorealistic video game Grand Theft Auto V developed by Rockstar North. It features 125,000 samples, all being a unique person, each of which is automatically labeled with information concerning visual attributes, as well as joint locations.


Details

  • 125K pairs of occluded and fully visible pedestrians
  • 24 attributes
  • 22 joint locations, with occlusion information


Download the Dataset

To obtain a copy of the dataset, please send an email to Ing. Matteo Fabbri (with object "AiC Dataset Download") stating:

  1. Your name, title and affilation
  2. Your intended use of the data
  3. The following statement
    With this email we declare that we will use the AiC Dataset for research and educational purposes only, since we are aware that commercial use is prohibited. We also undertake to purchase a copy of Grand Theft Auto V.


We will promptly reply with a download link and a detailed description of the structure of the provided annotations. You can find the GitHub repository 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.


Citation

We believe in open research and we are happy if you find this data useful. If you use it, please cite our works [1] [2].

@article{fulgeri2019can,
  title     = {Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?},
  author    = {Fulgeri, Federico and Fabbri, Matteo and Alletto, Stefano and Calderara, Simone and Cucchiara, Rita},
  journal   = {arXiv preprint arXiv:1901.08097},
  year      = {2019}
}

@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}
}