EPIC Fields: Marrying 3D Geometry and Video Understanding

Vadim Tschernezki*, Ahmad A K Dar Khalil*, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi

*Corresponding author for this work

Research output: Contribution to conferenceConference Paper

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Neural rendering is fuelling a unification of learning, 3D geometry and video understanding that has been waiting for more than two decades. Progress, however, is still hampered by a lack of suitable datasets and benchmarks. To address this gap, we introduce EPIC Fields, an augmentation of EPIC-KITCHENS with 3D camera information. Like other datasets for neural rendering, EPIC Fields removes the complex and expensive step of reconstructing cameras using photogrammetry, and allows researchers to focus on modelling problems. We illustrate the challenge of photogrammetry in egocentric videos of dynamic actions and propose innovations to address them. Compared to other neural rendering datasets, EPIC Fields is better tailored to video understanding because it is paired with labelled action segments and the recent VISOR segment annotations. To further motivate the community, we also evaluate two benchmark tasks in neural rendering and segmenting dynamic objects, with strong baselines that showcase what is not possible today. We also highlight the advantage of geometry in semi-supervised video object segmentations on the VISOR annotations. EPIC Fields reconstructs 96% of videos in EPIC-KITCHENS, registering 19M frames in 99 hours recorded in 45 kitchens, and is available from: http://epic-kitchens.github.io/epic-fields
Original languageEnglish
Publication statusPublished - 16 Dec 2023
EventConference on Neural Information Systems - Ernest N. Morial Convention Center, New Orleans, United States
Duration: 10 Dec 202316 Dec 2023


ConferenceConference on Neural Information Systems
Country/TerritoryUnited States
CityNew Orleans
Internet address


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