203 citations · 556 across the 17 of their papers we have counts for
7 papers · 1 filter
Example-based Motion Synthesis via Generative Motion Matching
Weiyu Li, Xuelin Chen, Peizhuo Li +2
We present GenMM, a generative model that "mines" as many diverse motions as possible from a single or few example sequences. In stark contrast to existing data-driven methods, whi…
Patch-based 3D Natural Scene Generation from a Single Example
Weiyu Li, Xuelin Chen, Jue Wang +1
We target a 3D generative model for general natural scenes that are typically unique and intricate. Lacking the necessary volumes of training data, along with the difficulties of h…
Learning Skeletal Articulations with Neural Blend Shapes
Peizhuo Li, Kfir Aberman, Rana Hanocka +3
Animating a newly designed character using motion capture (mocap) data is a long standing problem in computer animation. A key consideration is the skeletal structure that should c…
Unpaired Motion Style Transfer from Video to Animation
Kfir Aberman, Yijia Weng, Dani Lischinski +2
Transferring the motion style from one animation clip to another, while preserving the motion content of the latter, has been a long-standing problem in character animation. Most e…
Learning Elastic Constitutive Material and Damping Models
Bin Wang, Yuanmin Deng, Paul Kry +3
Commonly used linear and nonlinear constitutive material models in deformation simulation contain many simplifications and only cover a tiny part of possible material behavior. In…
Neural Material: Learning Elastic Constitutive Material and Damping Models from Sparse Data
Bin Wang, Paul Kry, Yuanmin Deng +3
The accuracy and fidelity of deformation simulations are highly dependent upon the underlying constitutive material model. Commonly used linear or nonlinear constitutive material m…