HOT3D

[linukc]

HOT3D is a new benchmark dataset for vision-based understanding of 3D hand-object interactions. This dataset contains over 800 minutes of egocentric recordings, with 33 diverse hand-held objects, capturing over one million multi-view frames of hand-object interactions.

Paper Project Code

@article{banerjee2024introducing,
  title={Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking},
  author={Banerjee, Prithviraj and Shkodrani, Sindi and Moulon, Pierre and Hampali, Shreyas and Zhang, Fan and Fountain, Jade and Miller, Edward and Basol, Selen and Newcombe, Richard and Wang, Robert and others},
  journal={arXiv preprint arXiv:2406.09598},
  year={2024}
}