5 papers
EMOSH: Expressive Motion and Shape Disentanglement for Human Animation
Dongbin Zhang, Hao Liu, Binquan Dai +5
High-fidelity and expressive controllable human animation is essential for content creation and digital avatar applications. However, existing methods face a dilemma between expres…
X-World: Controllable Ego-Centric Multi-Camera World Models for Scalable End-to-End Driving
Chaoda Zheng, Sean Li, Jinhao Deng +9
Scalable and reliable evaluation is increasingly critical in the end-to-end era of autonomous driving, where vision--language--action (VLA) policies directly map raw sensor streams…
Quantifying and Alleviating Co-Adaptation in Sparse-View 3D Gaussian Splatting
Kangjie Chen, Yingji Zhong, Zhihao Li +4
3D Gaussian Splatting (3DGS) has demonstrated impressive performance in novel view synthesis under dense-view settings. However, in sparse-view scenarios, despite the realistic ren…
SLGaussian: Fast Language Gaussian Splatting in Sparse Views
Kangjie Chen, BingQuan Dai, Minghan Qin +4
3D semantic field learning is crucial for applications like autonomous navigation, AR/VR, and robotics, where accurate comprehension of 3D scenes from limited viewpoints is essenti…
HRAvatar: High-Quality and Relightable Gaussian Head Avatar
Dongbin Zhang, Yunfei Liu, Lijian Lin +5
Reconstructing animatable and high-quality 3D head avatars from monocular videos, especially with realistic relighting, is a valuable task. However, the limited information from si…