Publications

Neural Garment Dynamics via Manifold-Aware Transformers

Data driven and learning based solutions for modeling dynamic garments have significantly advanced, especially in the context of …

Example-based Motion Synthesis via Generative Motion Matching

We present Generative Motion Matching (GenMM), a generative model that “mines” as many diverse motions as possible from a …

MoDi: Unconditional Motion Synthesis from Diverse Data

The emergence of neural networks revolutionized motion synthesis, yet synthesizing diverse motions remains challenging. We present …

GANimator: Neural Motion Synthesis from a Single Sequence

We present GANimator, a generative model that learns to synthesize novel motions from a single, short motion sequence. GANimator …

Learning Skeletal Articulations with Neural Blend Shapes

We develop a neural technique for articulating 3D characters using enveloping with a pre-defined skeletal structure, which is essential …

Skeleton-Aware Networks for Deep Motion Retargeting

We introduce a novel deep learning framework for data-driven motion retargeting between skeletons, which may have different structure, …