With this release, we aim to provide the tools the broader research community needs to explore ego-exo video, multimodal activity recognition, and beyond.

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Ego-Exo4D is a foundational dataset and benchmark suite for video learning and multimodal perception. It captures both egocentric and exocentric views to provide AI models with new insights into complex human skills. The dataset is the largest public dataset of time-synchronized first- and third-person video and includes audio, IMU, cameras, eye gaze, head poses, and 3D point cloud data. Ego-Exo4D aims to enable advancements in AI understanding of human skill, with applications ranging from augmented reality systems to robot learning and social networks.

Introducing Ego-Exo4D: A foundational dataset for research on video learning and multimodal perception