EPIC Fields Dataset and Benchmarks

Download Data

Downloading point clouds and camera poses

The dataset is now publicly available for download from here (7.5G).

Raw data in COLMAP format:

• The dense registered frames in raw COLMAP format can be found at: here (133G).
• The sparse frames including raw COLMAP database can be found at: here (91.6G).

Code

We provides the demo code for visualising the data, and the reconstruction pipeline:

• Visualisation and Pipeline

We make the following benchmark codes public, which replicate the EPIC Fields paper's baseline.

• Benchmark: NVS and UDOS provides the code to reproduce the results for Task 1 and Task 2.
• Benchmark: VOS contains the baselines for semi-supervised VOS (EPIC FIELDS).

Paper and Citation

When using these annotations, cite our paper (preprint now available on ArXiv):

@inproceedings{EPICFields2023,
           title={{EPIC Fields}: {M}arrying {3D} {G}eometry and {V}ideo {U}nderstanding},
           author={Tschernezki, Vadim and Darkhalil, Ahmad and Zhu, Zhifan and Fouhey, David and Larina, Iro and Larlus, Diane and Damen, Dima and Vedaldi, Andrea},
           booktitle   = {Proceedings of the Neural Information Processing Systems (NeurIPS)},
           year      = {2023}
} 

Also cite the EPIC-KITCHENS-100 paper where the videos originate:

@ARTICLE{Damen2022RESCALING,
           title={Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100},
           author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria  and and Furnari, Antonino 
           and Ma, Jian and Kazakos, Evangelos and Moltisanti, Davide and Munro, Jonathan 
           and Perrett, Toby and Price, Will and Wray, Michael},
           journal   = {International Journal of Computer Vision (IJCV)},
           year      = {2022},
           volume = {130},
           pages = {33–55},
           Url       = {https://doi.org/10.1007/s11263-021-01531-2}
} 

Disclaimer

The underlying data that power EPIC Fields, EPIC-KITCHENS-100, were collected as a tool for research in computer vision. The dataset may have unintended biases (including those of a societal, gender or racial nature).

Copyright

The EPIC Fields dataset is copyright by us and published under the Creative Commons Attribution-NonCommercial 4.0 International License. This means that you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.

For commercial licenses of EPIC-KITCHENS, email us at uob-epic-kitchens@bristol.ac.uk