Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estimation
Mariko Isogawa, Ye Yuan, Matthew O'Toole, Kris M. Kitani
2020年份
18顶会引用
摘要
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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引用它的顶会 Paper18
- PhysDiff: Physics-Guided Human Motion Diffusion ModelYe Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat 等ICCV 2023 · 被引用 414 次
- Physical Inertial Poser (PIP): Physics-aware Real-time Human Motion Tracking from Sparse Inertial SensorsXinyu Yi, Yuxiao Zhou, Marc Habermann, Soshi Shimada 等CVPR 2022 · 被引用 198 次
- Dynamics-regulated kinematic policy for egocentric pose estimationZhengyi Luo, Ryo Hachiuma, Ye Yuan, Kris KitaniNeurIPS 2021 · 被引用 130 次
- GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic CamerasYe Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani 等CVPR 2022 · 被引用 111 次
- Residual Force Control for Agile Human Behavior Imitation and Extended Motion SynthesisYe Yuan, Kris KitaniNeurIPS 2020 · 被引用 105 次
它引用的顶会 Paper2
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