Bingxuan Li | 李秉轩

Hi! I am a second-year Computer Science Ph.D. student at NYU, advised by Prof. Qi Sun in the Immersive Computing Lab.

My research interests are at the intersection of deep learning and computer graphics, focusing on 3D understanding, reconstruction, and generation. Recently, I have been working on physics-informed monocular depth estimation, pushing toward a better trade-off between size and accuracy in depth cameras. My goal is to enable compact and power-efficient depth sensing for size-sensitive scenarios such as AR glasses, small robotics, mobile devices, and wearable systems.

Prior to NYU, I received my Bachelor's degree with honors from Turing Class , Peking University . During my undergraduate years, I was honored to be advised by Prof. Sheng Li and Prof. Lingqi Yan.

I am actively seeking a research internship for Summer 2026!

Email  /  Github  /  CV  /  LinkedIn  /  WeChat  


profile photo

Research
* denotes equal contributions.
Nano-3D: Metasurface-Based Neural Depth Imaging
Bingxuan Li*, Jiahao Wu*, Yuan Xu*, Yunxiang Zhang, Zezheng Zhu, Nanfang Yu, Qi Sun
Paper
SIGGRAPH 2025 Emerging Technologies

We built a metasurface-based depth camera for accurate monocular metric depth estimation, combining polarization multiplexing with neural network decoding. The system was demonstrated in real time at SIGGRAPH 2025.

Image-GS: Content-Adaptive Image Representation via 2D Gaussians
Yunxiang Zhang*, Bingxuan Li*, Alexandr Kuznetsov, Akshay Jindal, Stavros Diolatzis, Kenneth Chen. Anton Sochenov, Anton Kaplanyan, Qi Sun
Paper / Project / Code
SIGGRAPH 2025

We present Image-GS, a content-adaptive neural image representation using anisotropic 2D Gaussians, offering high memory efficiency, fast random access, and flexible fidelity control for real-time graphics.

Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT
Fujia Su*, Bingxuan Li*, Qingyang Yin, Yanchen Zhang, Sheng Li
Paper / Project / Code / Video
ACM Transactions on Graphics (SIGGRAPH 2024)

We propose a novel sampling method to handle challenging specular/glossy paths in bidirectional path tracing (BDPT), significantly improving rendering efficiency while ensuring unbiasedness.


Selected Projects
EasyRender  Github

We present EasyRender, a scalable, high-performance ray tracing renderer built upon OptiX 8.0, featuring modular architecture, support for pbrt-v3 scenes and Disney Principled Materials, and implementations of advanced physically based rendering algorithms.

ROMA on Mitsuba  Github

This project explores the further applications of ROMA in rendering, implemented on Mitsuba 0.6. We primarily focused on enhancing the performance of ray tracing using ROMA, a novel acceleration method.


Services

Reviewer: SIGGRAPH Asia, TVCG


About Me

I enjoy reading, gaming, photography and other nerdy stuffs outside of work.


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