8 papers
Learning a Delighting Prior for Facial Appearance Capture in the Wild
Yuxuan Han, Xin Ming, Tianxiao Li +4
High-quality facial appearance capture has traditionally required costly studio recording. Recent works consider an in-the-wild smartphone-based setup; however, their model-based i…
WildCap: Facial Albedo Capture in the Wild via Hybrid Inverse Rendering
Yuxuan Han, Xin Ming, Tianxiao Li +4
Existing methods achieve high-quality facial albedo capture under controllable lighting, which increases capture cost and limits usability. We propose WildCap, a novel method for h…
Kinematify: Open-Vocabulary Synthesis of High-DoF Articulated Objects
Jiawei Wang, Dingyou Wang, Jiaming Hu +3
A deep understanding of kinematic structures and movable components is essential for enabling robots to manipulate objects and model their own articulated forms. Such understanding…
BANG: Dividing 3D Assets via Generative Exploded Dynamics
Longwen Zhang, Qixuan Zhang, Haoran Jiang +4
3D creation has always been a unique human strength, driven by our ability to deconstruct and reassemble objects using our eyes, mind and hand. However, current 3D design tools str…
Facial Appearance Capture at Home with Patch-Level Reflectance Prior
Yuxuan Han, Junfeng Lyu, Kuan Sheng +4
Existing facial appearance capture methods can reconstruct plausible facial reflectance from smartphone-recorded videos. However, the reconstruction quality is still far behind the…
Mojito: LLM-Aided Motion Instructor with Jitter-Reduced Inertial Tokens
Ziwei Shan, Yaoyu He, Chengfeng Zhao +5
Human bodily movements convey critical insights into action intentions and cognitive processes, yet existing multimodal systems primarily focused on understanding human motion via…