5 citations · 12 across the 11 of their papers we have counts for
11 papers
LPM 1.0: Video-based Character Performance Model
Ailing Zeng, Casper Yang, Chauncey Ge +22
Performance, the externalization of intent, emotion, and personality through visual, vocal, and temporal behavior, is what makes a character alive. Learning such performance from v…
TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization
Liang Pan, Zeshi Yang, Zhiyang Dou +5
Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods m…
Real-time Diverse Motion In-betweening with Space-time Control
Yuchen Chu, Zeshi Yang
In this work, we present a data-driven framework for generating diverse in-betweening motions for kinematic characters. Our approach injects dynamic conditions and explicit motion…
Learning based 2D Irregular Shape Packing
Zeshi Yang, Zherong Pan, Manyi Li +2
2D irregular shape packing is a necessary step to arrange UV patches of a 3D model within a texture atlas for memory-efficient appearance rendering in computer graphics. Being a jo…
Learning to Use Chopsticks in Diverse Gripping Styles
Zeshi Yang, KangKang Yin, Libin Liu
Learning dexterous manipulation skills is a long-standing challenge in computer graphics and robotics, especially when the task involves complex and delicate interactions between t…
Discovering Diverse Athletic Jumping Strategies
Zhiqi Yin, Zeshi Yang, Michiel van de Panne +1
We present a framework that enables the discovery of diverse and natural-looking motion strategies for athletic skills such as the high jump. The strategies are realized as control…
Efficient Hyperparameter Optimization for Physics-based Character Animation
Zeshi Yang, Zhiqi Yin
Physics-based character animation has seen significant advances in recent years with the adoption of Deep Reinforcement Learning (DRL). However, DRL-based learning methods are usua…
Learning and Exploring Motor Skills with Spacetime Bounds
Li-Ke Ma, Zeshi Yang, Xin Tong +2
Equipping characters with diverse motor skills is the current bottleneck of physics-based character animation. We propose a Deep Reinforcement Learning (DRL) framework that enables…
Neural fidelity warping for efficient robot morphology design
Sha Hu, Zeshi Yang, Greg Mori
We consider the problem of optimizing a robot morphology to achieve the best performance for a target task, under computational resource limitations. The evaluation process for eac…
Improving Skeleton-based Action Recognitionwith Robust Spatial and Temporal Features
Zeshi Yang, Kangkang Yin
Recently skeleton-based action recognition has made signif-icant progresses in the computer vision community. Most state-of-the-art algorithms are based on Graph Convolutional Netw…
Towards Robust Direction Invariance in Character Animation
Li-Ke Ma, Zeshi Yang, Baining Guo +1
In character animation, direction invariance is a desirable property. That is, a pose facing north and the same pose facing south are considered the same; a character that can walk…