EgoPoseVR Dataset Overview The EgoPoseVR Dataset is a large scale synthetic dataset for egocentric full body pose estimation in virtual reality. It contains paired RGB D observations, pose annotations, HMD tracking signals, and SMPL body parameters for temporally aligned motion clips. Total samples : 18,235 motion clips Scenes : 7 virtual scenes ( Scene0 Scene6 ) Train / Val / Test : 14,702 / 1,827 / 1,706 Data format : .npz (NumPy compressed archives) For more details, please visit the Project Page or check the official repository. Data Sources The motion data is derived from the AMASS dataset. In total, 2,344 motion sequences are extracted. Each sequence folder corresponds to one continuous motion sequence, and each .npz file contains a 100 frame clip sampled from that sequence. 🎬 Dataset Video Directory Structure Citation If you find our code or paper helps, please consider citing:
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