Pose-to-Motion: Cross-Domain Motion Retargeting with Pose Prior
We introduce a neural motion synthesis approach that uses accessible pose data to generate plausible character motions by transferring …
WalkTheDog: Cross-Morphology Motion Alignment via Phase Manifolds
We introduce a novel approach to learn a common phase manifold from motion datasets across different characters, such as human and dog, …
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, …
