EgoMM: Tri Modal Egocentric Dataset (Video + Audio + IMU) EgoMM is a large scale tri modal egocentric dataset combining Video, Audio, and IMU data from head mounted Meta Aria glasses. Built from EgoLife and Ego Exo4D sources. Dataset Summary Split EgoLife EgoExo4D Total Narration files narrated (val/test) 4,689 17,367 22,056 19,933 raw (train) 27,119 6,357 33,476 — Total 31,808 23,724 55,532 19,933 Clip duration : 30 seconds (fixed) Total hours : 463h Modalities : Video (MP4) + Audio (MP3) + IMU left/right (NPZ) Video resolution : EgoLife 768×768, EgoExo4D 448×448 Structure Download Narration Format Each narration.json contains clip relative annotations: Reconstructing Long Sequences Clips can be combined into longer sequences using sequence info : IMU Format Each NPZ file contains 7 arrays at 800Hz (left) or 1000Hz (right): timestamp : int64 nanoseconds accel x , accel y , accel z : float64, m/s² gyro x , gyro y , gyro z : float64, rad/s Activities (EgoExo4D) Activity Narrated clips Raw clips cooking ~7,800 ~3,600 music ~1,850 ~1,030 health ~1,950 ~560 bike repair ~1,470 ~260 dance ~1,200 ~380 rock climbing ~1,040 ~295 basketball ~935 ~316 soccer ~740 ~244 Participants (EgoLife) P…
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