May 16, 2024, 4:45 a.m. | Hiroyasu Akada, Jian Wang, Vladislav Golyanik, Christian Theobalt

cs.CV updates on arXiv.org arxiv.org

arXiv:2401.00889v2 Announce Type: replace
Abstract: While head-mounted devices are becoming more compact, they provide egocentric views with significant self-occlusions of the device user. Hence, existing methods often fail to accurately estimate complex 3D poses from egocentric views. In this work, we propose a new transformer-based framework to improve egocentric stereo 3D human pose estimation, which leverages the scene information and temporal context of egocentric stereo videos. Specifically, we utilize 1) depth features from our 3D scene reconstruction module with uniformly …

abstract arxiv compact cs.cv devices framework head human perception replace transformer type videos while work

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