Search Results for author:
Found 5 papers, 0 papers with code
AAMDM: Accelerated Auto-regressive Motion Diffusion Model
This paper introduces the Accelerated Auto-regressive Motion Diffusion Model (AAMDM), a novel motion synthesis framework designed to achieve quality, diversity, and efficiency all together.
Discovering Diverse Athletic Jumping Strategies
We present a framework that enables the discovery of diverse and natural-looking motion strategies for athletic skills such as the high jump.
Hierarchical Human Action Classification with Network Pruning
Research on human action classification has made significant progresses in the past few years.
Improving Skeleton-based Action Recognitionwith Robust Spatial and Temporal Features
Recently skeleton-based action recognition has made signif-icant progresses in the computer vision community.
Hierarchical Action Classification with Network Pruning
We test the effectiveness of our method on four commonly used testing datasets: NTU RGB+D 60, NTU RGB+D 120, Northwestern-UCLA Multiview Action 3D, and UTD Multimodal Human Action Dataset.
Ranked #5 on
Action Recognition
on NTU RGB+D
