EgoEdit: Dataset, Real Time Streaming Model, and Benchmark for Egocentric Video Editing Runjia Li 1,3 , Moayed Haji Ali 1,2 , Ashkan Mirzaei 1 , Chaoyang Wang 1 , Arpit Sahni 1 , Ivan Skorokhodov 1 , Aliaksandr Siarohin 1 , Tomas Jakab 3 , Junlin Han 3 , Sergey Tulyakov 1 , Philip Torr 3 , Willi Menapace 1 1 Snap Research, 2 Rice University, 3 University of Oxford Release Schedule Status Timeline Milestone : : : : : :white check mark: December 2025 Final review completed :white check mark: March 2026 Initial release of EgoEditData and EgoEditBench :arrows counterclockwise: TBD (soon) Code for EgoEditBench Overview We propose a framework for real time egocentric video editing. Our system is composed of three main components: EgoEditData : A manually curated dataset of 100k video editing pairs focusing on the egocentric case. It features object substitution and removal under challenging hand occlusions, interactions, and large egomotion. EgoEdit : The first real time autoregressive model for egocentric video editing. It runs in real time on a single H100 with 855ms first frame latency , enabling live augmented reality (AR) interactions. EgoEditBench : A comprehensive benchmark for th…
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