Weichuang Li

I am currently a Ph.D student at HKUST(GZ) , where I am supervised by Prof. Yuxuan Liang. I was an research assistant at Shanghai Artificial Intelligence Laboratory, where I work on computer vision and neural rendering.

I got my Master degree at City Univerisity of Hong Kong, studying Computer Science.

Email / Github

Research

My research interests include computer vision, neural rendering, and video processing.

	Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis Zhenhui Ye, Tianyun Zhong, Yi Ren, Jiaqi Yang, Weichuang Li, Jiawei Huang, Ziyue Jiang, Jinzheng He, Rongjie Huang, Jinglin Liu, Chen Zhang, Xiang Yin, Zejun MA, Zhou Zhao ICLR, 2024(Spotlight) Project page / Paper Real3D-Portrait is a framework that enhances one-shot 3D face reconstruction, accurate motion-conditioned animation, and audio-driven talking face generation, producing more realistic and versatile talking portrait videos than prior methods.
	Affordance-Driven Next-Best-View Planning for Robotic Grasping Xuechao Zhang, Dong Wang, Sun Han, Weichuang Li, Bin Zhao, Zhigang Wang, Xiaoming Duan, Chongrong Fang, Xuelong Li, Jianping He CoRL, 2023 Project page / Paper We introduce an AffordanCE-driven Next-Best-View planning policy (ACE-NBV) that tries to find a feasible grasp for target object via continuously observing scenes from new viewpoints.
	One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field Weichaung Li, Longhao Zhang, Dong Wang, Bin Zhao, Zhigang Wang, Mulin Chen, Bang Zhang, Zhongjian Wang, Liefeng Bo, Xuelong Li CVPR, 2023 Project page / arXiv We propose a deformable NeRF that is capable of generating high-fidelity talking portraits with single image input.
	Detection of GAN-Generated Images by Estimating Artifact Similarity Weichuang Li, Peisong He, Haoliang Li, Hongxia Wang, Ruimei Zhang IEEE Signal Processing Letters (SPL), 2021 Poster / PDF / Code We formulate the task of GAN-generated image detection as a problem of estimating how artifacts of the suspicious image are similar to GAN-generated images.

Thank JonBarron for this awesome template.