157 citations · 613 across the 45 of their papers we have counts for
49 papers
DROP: Dynamics Responses from Human Motion Prior and Projective Dynamics
Yifeng Jiang, Jungdam Won, Yuting Ye +1
Synthesizing realistic human movements, dynamically responsive to the environment, is a long-standing objective in character animation, with applications in computer vision, sports…
DiffusionPoser: Real-time Human Motion Reconstruction From Arbitrary Sparse Sensors Using Autoregressive Diffusion
Tom Van Wouwe, Seunghwan Lee, Antoine Falisse +2
Motion capture from a limited number of body-worn sensors, such as inertial measurement units (IMUs) and pressure insoles, has important applications in health, human performance,…
Hierarchical Planning and Control for Box Loco-Manipulation
Zhaoming Xie, Jonathan Tseng, Sebastian Starke +2
Humans perform everyday tasks using a combination of locomotion and manipulation skills. Building a system that can handle both skills is essential to creating virtual humans. We p…
CIRCLE: Capture In Rich Contextual Environments
Joao Pedro Araujo, Jiaman Li, Karthik Vetrivel +5
Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic activities people perform in the real world. However, conventional optics…
On Designing a Learning Robot: Improving Morphology for Enhanced Task Performance and Learning
Maks Sorokin, Chuyuan Fu, Jie Tan +5
As robots become more prevalent, optimizing their design for better performance and efficiency is becoming increasingly important. However, current robot design practices overlook…
Scene Synthesis from Human Motion
Sifan Ye, Yixing Wang, Jiaman Li +4
Large-scale capture of human motion with diverse, complex scenes, while immensely useful, is often considered prohibitively costly. Meanwhile, human motion alone contains rich info…
NeMo: 3D Neural Motion Fields from Multiple Video Instances of the Same Action
Kuan-Chieh Wang, Zhenzhen Weng, Maria Xenochristou +4
The task of reconstructing 3D human motion has wideranging applications. The gold standard Motion capture (MoCap) systems are accurate but inaccessible to the general public due to…
Physically Plausible Animation of Human Upper Body from a Single Image
Ziyuan Huang, Zhengping Zhou, Yung-Yu Chuang +2
We present a new method for generating controllable, dynamically responsive, and photorealistic human animations. Given an image of a person, our system allows the user to generate…
Ego-Body Pose Estimation via Ego-Head Pose Estimation
Jiaman Li, C. Karen Liu, Jiajun Wu
Estimating 3D human motion from an egocentric video sequence plays a critical role in human behavior understanding and has various applications in VR/AR. However, naively learning…
EDGE: Editable Dance Generation From Music
Jonathan Tseng, Rodrigo Castellon, C. Karen Liu
Dance is an important human art form, but creating new dances can be difficult and time-consuming. In this work, we introduce Editable Dance GEneration (EDGE), a state-of-the-art m…
Trajectory and Sway Prediction Towards Fall Prevention
Weizhuo Wang, Michael Raitor, Steve Collins +2
Falls are the leading cause of fatal and non-fatal injuries, particularly for older persons. Imbalance can result from the body's internal causes (illness), or external causes (act…
A Survey on Reinforcement Learning Methods in Character Animation
Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton +4
Reinforcement Learning is an area of Machine Learning focused on how agents can be trained to make sequential decisions, and achieve a particular goal within an arbitrary environme…
Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation
Yifeng Jiang, Yuting Ye, Deepak Gopinath +3
Real-time human motion reconstruction from a sparse set of (e.g. six) wearable IMUs provides a non-intrusive and economic approach to motion capture. Without the ability to acquire…
Real-time Model Predictive Control and System Identification Using Differentiable Physics Simulation
Sirui Chen, Keenon Werling, Albert Wu +1
Developing robot controllers in a simulated environment is advantageous but transferring the controllers to the target environment presents challenges, often referred to as the "si…
DASH: Modularized Human Manipulation Simulation with Vision and Language for Embodied AI
Yifeng Jiang, Michelle Guo, Jiangshan Li +3
Creating virtual humans with embodied, human-like perceptual and actuation constraints has the promise to provide an integrated simulation platform for many scientific and engineer…
BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach +11
We introduce BEHAVIOR, a benchmark for embodied AI with 100 activities in simulation, spanning a range of everyday household chores such as cleaning, maintenance, and food preparat…
Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration
Chen Wang, Claudia Pérez-D'Arpino, Danfei Xu +3
We present a method for learning a human-robot collaboration policy from human-human collaboration demonstrations. An effective robot assistant must learn to handle diverse human b…
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation
Yanchao Yang, Hanxiang Ren, He Wang +5
We describe an unsupervised domain adaptation method for image content shift caused by viewpoint changes for a semantic segmentation task. Most existing methods perform domain alig…
Characterizing Multidimensional Capacitive Servoing for Physical Human-Robot Interaction
Zackory Erickson, Henry M. Clever, Vamsee Gangaram +4
Towards the goal of robots performing robust and intelligent physical interactions with people, it is crucial that robots are able to accurately sense the human body, follow trajec…
Learning to Manipulate Amorphous Materials
Yunbo Zhang, Wenhao Yu, C. Karen Liu +2
We present a method of training character manipulation of amorphous materials such as those often used in cooking. Common examples of amorphous materials include granular materials…
Fast and Feature-Complete Differentiable Physics for Articulated Rigid Bodies with Contact
Keenon Werling, Dalton Omens, Jeongseok Lee +2
We present a fast and feature-complete differentiable physics engine, Nimble (nimblephysics.org), that supports Lagrangian dynamics and hard contact constraints for articulated rig…
Task-Specific Design Optimization and Fabrication for Inflated-Beam Soft Robots with Growable Discrete Joints
Ioannis Exarchos, Karen Wang, Brian H. Do +4
Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms,…
SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning
Yifeng Jiang, Tingnan Zhang, Daniel Ho +4
As learning-based approaches progress towards automating robot controllers design, transferring learned policies to new domains with different dynamics (e.g. sim-to-real transfer)…
Protective Policy Transfer
Wenhao Yu, C. Karen Liu, Greg Turk
Being able to transfer existing skills to new situations is a key capability when training robots to operate in unpredictable real-world environments. A successful transfer algorit…