90 citations · 260 across the 22 of their papers we have counts for
22 papers
Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion
Davis Rempe, Zhengyi Luo, Xue Bin Peng +5
We introduce a method for generating realistic pedestrian trajectories and full-body animations that can be controlled to meet user-defined goals. We draw on recent advances in gui…
PhysDiff: Physics-Guided Human Motion Diffusion Model
Ye Yuan, Jiaming Song, Umar Iqbal +2
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…
From Universal Humanoid Control to Automatic Physically Valid Character Creation
Zhengyi Luo, Ye Yuan, Kris M. Kitani
Automatically designing virtual humans and humanoids holds great potential in aiding the character creation process in games, movies, and robots. In some cases, a character creator…
Embodied Scene-aware Human Pose Estimation
Zhengyi Luo, Shun Iwase, Ye Yuan +1
We propose embodied scene-aware human pose estimation where we estimate 3D poses based on a simulated agent's proprioception and scene awareness, along with external third-person o…
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation
Yanglan Ou, Ye Yuan, Xiaolei Huang +4
We present a new encoder-decoder Vision Transformer architecture, Patcher, for medical image segmentation. Unlike standard Vision Transformers, it employs Patcher blocks that segme…
Online No-regret Model-Based Meta RL for Personalized Navigation
Yuda Song, Ye Yuan, Wen Sun +1
The interaction between a vehicle navigation system and the driver of the vehicle can be formulated as a model-based reinforcement learning problem, where the navigation systems (a…
GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
Ye Yuan, Umar Iqbal, Pavlo Molchanov +2
We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions and tracks h…
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Ye Yuan, Yuda Song, Zhengyi Luo +2
An agent's functionality is largely determined by its design, i.e., skeletal structure and joint attributes (e.g., length, size, strength). However, finding the optimal agent desig…
Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation
Zhengyi Luo, Ryo Hachiuma, Ye Yuan +1
We propose a method for object-aware 3D egocentric pose estimation that tightly integrates kinematics modeling, dynamics modeling, and scene object information. Unlike prior kinema…
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images
Yanglan Ou, Ye Yuan, Xiaolei Huang +4
Diffusion-weighted (DW) magnetic resonance imaging is essential for the diagnosis and treatment of ischemic stroke. DW images (DWIs) are usually acquired in multi-slice settings wh…
SimPoE: Simulated Character Control for 3D Human Pose Estimation
Ye Yuan, Shih-En Wei, Tomas Simon +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 d…
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
Ye Yuan, Xinshuo Weng, Yanglan Ou +1
Predicting accurate future trajectories of multiple agents is essential for autonomous systems, but is challenging due to the complex agent interaction and the uncertainty in each…
Efficient Non-Line-of-Sight Imaging from Transient Sinograms
Mariko Isogawa, Dorian Chan, Ye Yuan +2
Non-line-of-sight (NLOS) imaging techniques use light that diffusely reflects off of visible surfaces (e.g., walls) to see around corners. One approach involves using pulsed lasers…
Residual Force Control for Agile Human Behavior Imitation and Extended Motion Synthesis
Ye Yuan, Kris Kitani
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…
Semi-Supervised Cervical Dysplasia Classification With Learnable Graph Convolutional Network
Yanglan Ou, Yuan Xue, Ye Yuan +4
Cervical cancer is the second most prevalent cancer affecting women today. As the early detection of cervical carcinoma relies heavily upon screening and pre-clinical testing, digi…
Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation
Mariko Isogawa, Ye Yuan, Matthew O'Toole +1
We describe a method for 3D human pose estimation from transient images (i.e., a 3D spatio-temporal histogram of photons) acquired by an optical non-line-of-sight (NLOS) imaging sy…
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
Ye Yuan, Kris Kitani
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…
PTP: Parallelized Tracking and Prediction with Graph Neural Networks and Diversity Sampling
Xinshuo Weng, Ye Yuan, Kris Kitani
Multi-object tracking (MOT) and trajectory prediction are two critical components in modern 3D perception systems that require accurate modeling of multi-agent interaction. We hypo…
Diverse Trajectory Forecasting with Determinantal Point Processes
Ye Yuan, Kris Kitani
The ability to forecast a set of likely yet diverse possible future behaviors of an agent (e.g., future trajectories of a pedestrian) is essential for safety-critical perception sy…
Ego-Pose Estimation and Forecasting as Real-Time PD Control
Ye Yuan, Kris Kitani
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. The…
Generative Hybrid Representations for Activity Forecasting with No-Regret Learning
Jiaqi Guan, Ye Yuan, Kris M. Kitani +1
Automatically reasoning about future human behaviors is a difficult problem but has significant practical applications to assistive systems. Part of this difficulty stems from lear…
Interactive Co-Design of Form and Function for Legged Robots using the Adjoint Method
Ruta Desai, Beichen Li, Ye Yuan +1
Our goal is to make robotics more accessible to casual users by reducing the domain knowledge required in designing and building robots. Towards this goal, we present an interactiv…