Runfeng Li

Hi, I'm a M.S. student in Computer Science at Brown University. I'm fortunate to work with Prof. James Tompkin.

Research

I'm interested in computer vision, computational imaging, and computer graphics.

Time of the Flight of the Gaussians: Optimizing Depth Indirectly in Dynamic Radiance Fields
Runfeng Li, Mikhail Okunev, Zixuan Guo, Anh Ha Duong, Christian Richardt, Matthew O'Toole, James Tompkin
CVPR, 2025
project page / paper / code (coming soon)
Also at NECV workshop, 2024

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.

Monocular Dynamic Gaussian Splatting is Fast and Brittle but Smooth Motion Helps
Yiqing Liang, Mikhail Okunev, Mikaela Angelina Uy, Runfeng Li, Leonidas J. Guibas, James Tompkin, Adam Harley
In Review, 2025
project page / paper

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

More on Github

	3D Gaussian Physics Simulation and Material Elasticity Reconstruction code / presentation 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.]
	Gradient Domain High Dynamic Range Compression in CUDA code 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.