activity
20232026
most citedConditional GAN for Enhancing Diffusion Models in Efficient and Authentic Global Gesture Generation from Audios

1 citations · 2 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Mirage2Matter: A Physically Grounded Gaussian World Model from Video

Zhengqing Gao, Ziwen Li, Xin Wang +12

The scalability of embodied intelligence is fundamentally constrained by the scarcity of real-world interaction data. While simulation platforms provide a promising alternative, ex…

cs.CV2025

Towards Reliable Human Evaluations in Gesture Generation: Insights from a Community-Driven State-of-the-Art Benchmark

Rajmund Nagy, Hendric Voss, Thanh Hoang-Minh +18

We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed experimental setups. This leads…

cs.GR2025

Inter-Diffusion Generation Model of Speakers and Listeners for Effective Communication

Jinhe Huang, Yongkang Cheng, Yuming Hang +4

Full-body gestures play a pivotal role in natural interactions and are crucial for achieving effective communication. Nevertheless, most existing studies primarily focus on the ges…

cs.CV2025

HoloGest: Decoupled Diffusion and Motion Priors for Generating Holisticly Expressive Co-speech Gestures

Yongkang Cheng, Shaoli Huang

Animating virtual characters with holistic co-speech gestures is a challenging but critical task. Previous systems have primarily focused on the weak correlation between audio and…

cs.CV2025

From 2D Alignment to 3D Plausibility: Unifying Heterogeneous 2D Priors and Penetration-Free Diffusion for Occlusion-Robust Two-Hand Reconstruction

Gaoge Han, Yongkang Cheng, Zhe Chen +2

Two-hand reconstruction from monocular images is hampered by complex poses and severe occlusions, which often cause interaction misalignment and two-hand penetration. We address th…

cs.SD20241 cited

Conditional GAN for Enhancing Diffusion Models in Efficient and Authentic Global Gesture Generation from Audios

Yongkang Cheng, Mingjiang Liang, Shaoli Huang +3

Audio-driven simultaneous gesture generation is vital for human-computer communication, AI games, and film production. While previous research has shown promise, there are still li…