Runfeng Li

Hi, I'm a Master's student in Computer Science at Brown University, where I'm fortunate to work with Prof. James Tompkin on reconstruction and imaging at the Brown Visual Computing Group.

Previously, I received my Bachelor's degree in Mathematics and Computer Science from University of Illinois Urbana-Champaign, where I was fortunate to work with Prof. Liangyan Gui on deep learning and human motion modeling.

Email  /  CV  /  Google Scholar  /  Github

Research

I'm interested in computer vision and its intersection with computational imaging, computer graphics, and machine learning.

Depth optimization via C-ToF radiance field is indirect and ambiguous. Interestingly, two biases can help escape unwanted local optima. Our GS-based system trains and renders 100x faster, too.

We benchmark dynamic GS methods, combining existing datasets and a new synthetic dataset to provide standardized comparisons and identify key factors affecting efficiency and quality.

Projects

We implement PhysGaussian using Taichi, and reconstruct material elasticity from multi-view videos through the differentiable GS rendering and MPM simulation system.
[← Click to toggle sim/recon.]

We implement Poisson PDE solvers for the gradient domain HDR compression method in CUDA/C++. Tonemapping is real-time (100+ Hz) for HD images.
[← Gamma v.s. HDRC, planning to finetune the parameters and refine the result a bit]

Based on Jon Barron's template.