News

What is EPIC-KITCHENS-100?

The extended largest dataset in first-person (egocentric) vision; multi-faceted, audio-visual, non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities in the kitchen over multiple days. Annotations are collected using a novel 'Pause-and-Talk' narration interface.

Characteristics

  • 45 kitchens - 4 cities
  • Head-mounted camera
  • 100 hours of recording - Full HD
  • 20M frames
  • Multi-language narrations
  • 90K action segments
  • 20K unique narrations
  • 90 verb classes, 300 noun classes
  • 6 challenges

Previous versions...

EPIC-KITCHENS-100 Stats and Figures

Some graphical representations of our dataset and annotations

Annotation Pipeline

Automatic Annotations

Download

Dataset publicly available for research purposes

Data and Download Script

Extended Sequences (+RGB Frames, Flow Frames, Gyroscope + accelerometer data): Available at Data.Bris servers (740GB zipped) or via Academic Torrents

Original Sequences (+RGB and Flow Frames): Available at Data.Bris servers (1.1TB zipped) or via Academic Torrents

We also offer a python script to download various parts of the dataset

Annotations and Pipeline

All annotations (Train/Val/Test) for all challenges are available at EPIC-KITCHENS-100-annotations repo

Code to visualise and utilise automatic annotations is available for both object masks and hand-object detections.

The EPIC Narrator, used to collect narrations for EPIC-KITCHENS-100 is open-sourced at EPIC-Narrator repo

Publication(s)

Cite the extension's ArXiv paper (available now on Arxiv):

@ARTICLE{Damen2020RESCALING,
   title={Rescaling Egocentric Vision},
   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   = {CoRR},
           volume    = {abs/2006.13256},
           year      = {2020},
           ee        = {http://arxiv.org/abs/2006.13256},
} 

Additionally, cite the original paper (available now on Arxiv and the CVF):

@INPROCEEDINGS{Damen2018EPICKITCHENS,
   title={Scaling Egocentric Vision: The EPIC-KITCHENS Dataset},
   author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria  and Fidler, Sanja and 
           Furnari, Antonino and Kazakos, Evangelos and Moltisanti, Davide and Munro, Jonathan 
           and Perrett, Toby and Price, Will and Wray, Michael},
   booktitle={European Conference on Computer Vision (ECCV)},
   year={2018}
} 

A journal version of the ECCV 2018 paper is (available now on Arxiv and IEEE Early Access):

@ARTICLE{Damen2020Collection,
   title={The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines},
   author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria  and Fidler, Sanja and 
           Furnari, Antonino and Kazakos, Evangelos and Moltisanti, Davide and Munro, Jonathan 
           and Perrett, Toby and Price, Will and Wray, Michael},
   journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
   year={2020}
} 

Copyright Creative Commons License

All datasets and benchmarks on this page are 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.

EPIC-KITCHENS-100 2021 Challenges

Challenge and Leaderboard Details COMING SOON

The Team

We are a group of researchers working in computer vision from the University of Bristol and University of Catania. The original dataset was collected in collaboration with Sanja Fidler, University of Toronto

Dima Damen

Principal Investigator
University of Bristol, United Kingom

Giovanni Maria Farinella

Co-I
University of Catania, Italy

Davide Moltisanti

(Apr 2017 - )
(prev.) University of Bristol
(curr.) Nanyang Tech University

Michael Wray

(Apr 2017 - )
University of Bristol

Hazel Doughty

(Apr 2017 - )
University of Bristol

Toby Perrett

(Apr 2017 - )
University of Bristol

Antonino Furnari

(Jul 2017 - )
University of Catania

Jonathan Munro

(Sep 2017 - )
University of Bristol

Evangelos Kazakos

(Sep 2017 - )
University of Bristol

Will Price

(Oct 2017 - )
University of Bristol

Jian Ma

(Sep 2019 - )
University of Bristol

Research Funding

The work on extending EPIC-KITCHENS was supported by the following research grants