Ego 1K — A Large Scale Multiview Video Dataset for Egocentric Vision Jae Yong Lee, Daniel Scharstein, Akash Bapat, Hao Hu, Andrew Fu, Haoru Zhao, Paul Sammut, Xiang Li, Stephen Jeapes, Anik Gupta, Lior David, Saketh Madhuvarasu, Jay Girish Joshi, and Jason Wither arxiv.org/abs/2603.13741; to appear in CVPR 2026 We present Ego 1K, a large scale collection of time synchronized egocentric multiview videos designed to advance neural 3D video synthesis and dynamic scene understanding. The dataset contains 956 short (6.7 9.7s) egocentric videos taken with a custom rig with 12 synchronous cameras surrounding a VR headset worn by the user, for a total of 491K frames and 5.9M images. Scene content focuses on hand motions and hand object interactions in different settings. Our dataset enables new ways to benchmark egocentric scene reconstruction methods, and presents unique challenges for existing 3D and 4D novel view synthesis methods due to high disparities and image motion caused by close dynamic objects and rig egomotion. License FAIR Noncommercial Research License Getting Started See quickstart.ipynb for a runnable walkthrough that loads metadata, streams images, and visualizes a 12 cam…
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