Ye YuanShow more

Ye Yuan , Shih-En Wei, Tomas Simon, Kris Kitani, Jason Saragih Conference on Computer Vision and Pa ern Recognition (CVPR), 2021 (Oral Presentation – Top 4.2%)

Accurate estimation of 3D human motion from monocular video requires modeling both kinematics (body motion without physical forces) and dynamics (motion with physical forces). To …

Reinforcement learning has shown great promise for synthesizing realistic human behaviors by learning humanoid control policies from motion capture data. However, it is still very …

We propose the use of a proportional-derivative (PD) control based policy learned via reinforcement learning (RL) to estimate and forecast 3D human pose from egocentric videos. …

Denoising diffusion models hold great promise for generating diverse and realistic human motions. However, existing motion diffusion models largely disregard the laws of physics in the …

Deep generative models are often used for human motion prediction as they are able to model multi-modal data distributions and characterize diverse human behavior. While much care has …

Predicting accurate future trajectories of multiple agents is essential for autonomous systems, but is challenging due to the complex interaction between agents and the uncertainty in each …

Summary We developed a fast distributed GPU ray tracer that has the following features: Very Fast Ray Traversal Even for scenes with 100K+ triangles, our ray tracer can achieve a …