3 citations · 9 across the 10 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.CV2023
DiffusionPhase: Motion Diffusion in Frequency Domain
Weilin Wan, Yiming Huang, Shutong Wu +4
In this study, we introduce a learning-based method for generating high-quality human motion sequences from text descriptions (e.g., ``A person walks forward"). Existing techniques…
cs.CV2023★ 3 cited
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
Wenyang Zhou, Zhiyang Dou, Zeyu Cao +7
We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation. Current state-of-the-art generative diffusion models have produced impressiv…
cs.CV2023
TLControl: Trajectory and Language Control for Human Motion Synthesis
Weilin Wan, Zhiyang Dou, Taku Komura +3
Controllable human motion synthesis is essential for applications in AR/VR, gaming and embodied AI. Existing methods often focus solely on either language or full trajectory contro…