2 citations · 2 across the 13 of their papers we have counts for
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cs.CV2025
Multi-Modal Motion Retrieval by Learning a Fine-Grained Joint Embedding Space
Shiyao Yu, Zi-An Wang, Kangning Yin +4
Motion retrieval is crucial for motion acquisition, offering superior precision, realism, controllability, and editability compared to motion generation. Existing approaches levera…
cs.CV2024
RACon: Retrieval-Augmented Simulated Character Locomotion Control
Yuxuan Mu, Shihao Zou, Kangning Yin +4
In computer animation, driving a simulated character with lifelike motion is challenging. Current generative models, though able to generalize to diverse motions, often pose challe…
cs.CV2024★ 2 cited
Tri-Modal Motion Retrieval by Learning a Joint Embedding Space
Kangning Yin, Shihao Zou, Yuxuan Ge +1
Information retrieval is an ever-evolving and crucial research domain. The substantial demand for high-quality human motion data especially in online acquirement has led to a surge…