Bio

I am currently a PhD student at the Center for Visual Computing at UC San Diego, advised by professor Ravi Ramamoorthi and also working with professor Tzu-Mao Li. My research primarily focuses on physically based rendering, especially forward&inverse light transport simulation and sampling problems. Previously, I obtained my bachelor's degree in CS from the University of Hong Kong and worked a bit on knowledge-based question answering systems.

I have had the fortune to intern at Adobe Graphics Research and Meta Reality Labs for the past couple of summers, working with amazing mentors and colleagues.

Before PhD, I worked as a rendering research engineer at ZJU-Manycore Tech joint Lab of CG&AI, led by Dr. Rui Tang and Prof. Rui Wang, where I mainly worked on our self-developed Render Engine FF (aka fast and furious :P), Monte Carlo sampling, denoising and other graphics related topics. During the interest exploration phase of my undergraduate, I spent half a year in freezing Ottawa, Canada, working on unified model language, and also spent a short time at Alibaba and Sensetime on stream processing and face recognition, respectively.

Research

I am mainly interested in physically-based rendering, especially light transport simulation, stochastic sampling and learning approaches for appearance modelling etc. Recently I'm very interested in optimization problems.

Residual Path Integrals for Re-Rendering
Bing Xu, Tzu-Mao Li, Iliyan Georgiev, Trevor Hedstrom, Ravi Ramamoorthi
Computer Graphics Forum (Proceedings of Eurographics Symposium on Rendering), 2024
Best Paper Award
project page / paper / code (coming)

Incremental re-rendering of scenes in a common senario where only a small portion is moving or edited (e.g. the main character hanging around in an open world).
Formulating the difference between two frames as a (correlated) light-transport integral. Devising sampling strategies to focus on paths with non-zero residual-radiance contribution and tailoring appropriate path mappings.
We welcome increased attention to the exploration and potential optimization of the residual path integral and, overall, the re-rendering problem.

Importance Sampling BRDF Derivatives
Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li
ACM Transactions on Graphics (TOG), 2024
project page / paper

Yash's great work on importance sampling real-valued derivates, enabling better recovery of spatially varying textures through GD-based inverse rendering.

Neusample: Importance Sampling for Neural Materials
Bing Xu, Liwen Wu, Miloš Hašan, Fujun Luan, Iliyan Georgiev, Zexiang Xu, Ravi Ramamoorthi
ACM SIGGRAPH, 2023
project page / paper / code

A simple toolbox composed of three approaches to efficiently importance sample neural SVBRDFs, potentially facilitating the broader adoption of neural material models in production.

Adversarial Monte Carlo Denoising with Conditioned Auxiliary Feature Modulation
Bing Xu, Junfei Zhang, Rui Wang, Kun Xu, Yong-liang Yang, Chuan Li, Rui Tang
ACM Transactions on Graphics (TOG), ACM SIGGRAPH Asia, 2019
project page / paper / code

Denoising Monte Carlo renderings by better utilizing the first bounce auxiliary features and adversarial loss.

Gallery

, if it can be called A Gallery.... I do some drawing and painting when I'm struggling with research. I might stop doing research once my paintings start making money - you know, the best-case scenario I can think of, after the painter's death.

These photos were taken randomly so the resolution may not be good.

Miscellany

• Zombies, see you later.