119 citations · 324 across the 15 of their papers we have counts for
16 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…
Physics-based Motion Retargeting from Sparse Inputs
Daniele Reda, Jungdam Won, Yuting Ye +2
Avatars are important to create interactive and immersive experiences in virtual worlds. One challenge in animating these characters to mimic a user's motion is that commercial AR/…
QuestEnvSim: Environment-Aware Simulated Motion Tracking from Sparse Sensors
Sunmin Lee, Sebastian Starke, Yuting Ye +2
Replicating a user's pose from only wearable sensors is important for many AR/VR applications. Most existing methods for motion tracking avoid environment interaction apart from fo…
Simulation and Retargeting of Complex Multi-Character Interactions
Yunbo Zhang, Deepak Gopinath, Yuting Ye +3
We present a method for reproducing complex multi-character interactions for physically simulated humanoid characters using deep reinforcement learning. Our method learns control p…
AlteredAvatar: Stylizing Dynamic 3D Avatars with Fast Style Adaptation
Thu Nguyen-Phuoc, Gabriel Schwartz, Yuting Ye +2
This paper presents a method that can quickly adapt dynamic 3D avatars to arbitrary text descriptions of novel styles. Among existing approaches for avatar stylization, direct opti…
Learning to Transfer In-Hand Manipulations Using a Greedy Shape Curriculum
Yunbo Zhang, Alexander Clegg, Sehoon Ha +2
In-hand object manipulation is challenging to simulate due to complex contact dynamics, non-repetitive finger gaits, and the need to indirectly control unactuated objects. Further…