| CARVIEW |
Biography
PhD student in Visual and Data Intelligence Center(VDI), School of Information Science and Technology(SIST), ShanghaiTech University.
I am a final-year PhD student in Computer Science at ShanghaiTech University, working with Prof. Jingyi Yu. I also work closely with Prof. Lan Xu. I received my bachelor’s degree in 2019 from Huazhong University of Science and Technology.
I am honored to be collaborating with Fernando De la Torre as a visiting scholar currently at the CMU Human Sensing Lab.
My research interest lies in Neural Modeling and Rendering, 3D Reconstruction, Motion Capture and Animation, Digital Human and Animals. Download my resumé .
I’m looking for an internship or a postdoctoral position.
- Computer Vision
- Computer Graphics
- Artificial Intelligence
-
PhD in Computer Science and Technology, 2025
ShanghaiTech University
-
MEng in Computer Science and Technology, 2022
ShanghaiTech University
-
BSc in Computer Science and Technology, 2019
Huazhong University of Science and Technology
Experience
Featured Publications
This paper presents GaussianHair, a novel explicit hair representation. It enables comprehensive modeling of hair geometry and appearance from images, fostering innovative illumination effects and dynamic animation capabilities.
We construct a dense multi-view dome to acquire a complex human object interaction dataset, named HODome, that consists of ∼71M frames on 10 subjects interacting with 23 objects. To process the HODome dataset, we develop NeuralDome, a layer-wise neural processing pipeline tailored for multi-view video inputs to conduct accurate tracking, geometry reconstruction and free-view rendering, for both human subjects and objects.
In this paper, we resort to cloud rendering and present NEPHELE, a neural platform for highly realistic cloud radiance rendering. In stark contrast with existing NR approaches, our NEPHELE allows for more powerful rendering capabilities by combining multiple remote GPUs, and facilitates collaboration by allowing multiple people to view the same NeRF scene simultaneously.
We present ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS. Our ARTEMIS enables interactive motion control, real-time animation and photo-realistic rendering of furry animals.
We propose a novel scheme to generate opacity radiance fields with a convolutional neural renderer for fuzzy objects with high feaqurncy details.
Recent Publications
Contact
- luohm@@shanghaitech.edu.cn
- 393 Middle Huaxia Road, Pudong, Shanghai 201210
- DM Me