My research interests focus on the intersection of 3D computer vision and computer graphics, particularly developing machine learning tools to enable 3D content creation at scale and making impact in real-world applications.
I graduated from Peking University in 2018 with a Bachelor degree. I also interned in Stanford, MSRA and NVIDIA.
Pro Bono: I decide to commit 1-2 hours per week (mostly on Sunday) to host pro bono office hours and provide guidance, suggestions or mentorship for students, especially people from underrepresented groups, please fill this form if you are interested. More details is here.
May 2023: I will server as an Area Chair for NeurIPS 2023.
April 2023: I gave talk at PKU, THU, MSRA, CUHK (Shenzhen) on Machine Learning for 3D Content Creation.
April 2023: One paper is accepted to SIGGRAPH 2023 on flexible and differentiable iso-surfacing.
March 2023: Two papers are accepted to CVPR 2023 on text to 3D generation, and inverse rendering for scene.
March 2023: Invited talk at ETH, Oxford, JHU, UofT.
Selected Publications
My research contributes to the fundamental problems in 3D content creation, from the 3D representation, to learning algorithm, and to interactive control with texts. My research enables generating high quality 3D meshes with textures and arbitrary topologies, from multi-view images, in a generative model, or from text prompts. Many of my work have been successfully deployed in real-world applications, including NVIDIA Picasso, GANVerse3D, Neural DriveSim, Toronto Annotation Suite etc.
Representative papers are highlighted, with full publication list in Google Scholar.
Towards Generative Modeling of 3D Objects Learned from Images.
ETH, Oxford, JHU, UofT, PKU, BAAI (2023)
Learning Geometric Representation for Computer Vision. (GAMES-CN) Chinese [Link] (2020)
Learning Geometric Representation from Images. University of Alberta (2020)
Mentored Students/Interns
Tianchang Shen (PhD, CS UofT) Working on differentiable isosurfacing methods.
Weiwei Sun (PhD, CS UBC) Working on 3D generative models.
Zian Wang (PhD, CS UofT) Working on lighting decomposition with differentiable renderers.
Jinchen Xuan (Undergrad, CS PKU) Working on geometric image representation.
Gary Leung (MSc, CS UofT) Working on Transformer for images.
Pro bono office hours
As a fifth-year PhD student, I always see the information asymmetry between junior students and senior students,researchers or professors on problems related to research topics/directions, future career, and failure (and also excitement!) in research. This problem is more severe for people from underrepresented group.
Following Krishna, Wei-Chiu and Shangzhe, I decide to commit 1-2 hours per week (mostly on Sunday) to host pro bono office hours and provide guidance, suggestions or mentorship to reduce the information asymmetry mentioned above, please fill this form if you are interested.