5 citations · 7 across the 7 of their papers we have counts for
7 papers
ExecVLA: Following Fine-Grained Execution Constraints in Vision-Language-Action Models with Bi-Level Action Representation
Gaoge Han, Zhengqing Gao, Ziwen Li +5
We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must follow instruction-specified execution co…
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…
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…
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…
ReinDiffuse: Crafting Physically Plausible Motions with Reinforced Diffusion Model
Gaoge Han, Mingjiang Liang, Jinglei Tang +3
Generating human motion from textual descriptions is a challenging task. Existing methods either struggle with physical credibility or are limited by the complexities of physics si…
ExpGest: Expressive Speaker Generation Using Diffusion Model and Hybrid Audio-Text Guidance
Yongkang Cheng, Mingjiang Liang, Shaoli Huang +3
Existing gesture generation methods primarily focus on upper body gestures based on audio features, neglecting speech content, emotion, and locomotion. These limitations result in…
HuTuMotion: Human-Tuned Navigation of Latent Motion Diffusion Models with Minimal Feedback
Gaoge Han, Shaoli Huang, Mingming Gong +1
We introduce HuTuMotion, an innovative approach for generating natural human motions that navigates latent motion diffusion models by leveraging few-shot human feedback. Unlike exi…