activity
20242026
most citedLodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization

Ronghui Li, Zhongyuan Hu, Li Siyao +6

Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing method…

cs.CV2025

SpeakerVid-5M: A Large-Scale High-Quality Dataset for Audio-Visual Dyadic Interactive Human Generation

Youliang Zhang, Zhaoyang Li, Duomin Wang +6

The rapid development of large-scale models has catalyzed significant breakthroughs in the digital human domain. These advanced methodologies offer high-fidelity solutions for avat…

cs.CV2024

A Plug-and-Play Physical Motion Restoration Approach for In-the-Wild High-Difficulty Motions

Youliang Zhang, Ronghui Li, Yachao Zhang +4

Extracting physically plausible 3D human motion from videos is a critical task. Although existing simulation-based motion imitation methods can enhance the physical quality of dail…

cs.CV2024

InterDance:Reactive 3D Dance Generation with Realistic Duet Interactions

Ronghui Li, Youliang Zhang, Yachao Zhang +6

Humans perform a variety of interactive motions, among which duet dance is one of the most challenging interactions. However, in terms of human motion generative models, existing w…

cs.CV2024★ 1 cited

Lodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns

Ronghui Li, Hongwen Zhang, Yachao Zhang +6

We propose Lodge++, a choreography framework to generate high-quality, ultra-long, and vivid dances given the music and desired genre. To handle the challenges in computational eff…