Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estimation
Mariko Isogawa, Ye Yuan, Matthew O'Toole, Kris M. Kitani
Abstract
Hidden person Occluder Imaging system Photon measurements Estimated 3D human poses Wall Frames Figure 1. Non-Line-of-Sight (NLOS) Physics-Based 3D Human Pose Estimation. A pulsed laser and a transient sensor record the time light takes to travel from a point on a wall to the person hidden from sight (left). Given a sequence of 3D transient measurements from an optical NLOS system (top right), our method estimates a 3D pose sequence using a physics-based policy (bottom right).
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Install the CLIlune papers fulltext 998863c9-9381-4c1c-9a39-e1596949186cCited by top-tier papers18
- PhysDiff: Physics-Guided Human Motion Diffusion ModelYe Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat et al.ICCV 2023 · 414 citations
- Physical Inertial Poser (PIP): Physics-aware Real-time Human Motion Tracking from Sparse Inertial SensorsXinyu Yi, Yuxiao Zhou, Marc Habermann, Soshi Shimada et al.CVPR 2022 · 198 citations
- Dynamics-regulated kinematic policy for egocentric pose estimationZhengyi Luo, Ryo Hachiuma, Ye Yuan, Kris KitaniNeurIPS 2021 · 130 citations
- GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic CamerasYe Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani et al.CVPR 2022 · 111 citations
- Residual Force Control for Agile Human Behavior Imitation and Extended Motion SynthesisYe Yuan, Kris KitaniNeurIPS 2020 · 105 citations
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