Ang Li

I am a MSCS student at Stanford University. Previously I was an undergraduate student major in computer science at UC San Diego. I was fortunate to be advised by Prof. Hao Su.

I am broadly interested in computer vision, robotics and computer graphics.

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Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation
Xiaoshuai Zhang, Rui Chen, Ang Li, Fanbo Xiang, Yuzhe Qin, Jiayuan Gu, Zhan Ling, Minghua Liu, Peiyu Zeng, Songfang Han, Zhiao Huang, Tongzhou Mu, Jing Xu, Hao Su
T-RO, 2023
project page / arXiv

We lower the sim-to-real gap of simulated depth and real active stereovision depth sensors, by designing a fully physics-grounded pipeline. Perception and RL methods trained in simulation can transfer well to the real world without any fine-tuning. It can also estimate the algorithm performance in the real world, largely reducing human effort of algorithm evaluation.

SimSense: A Real-Time Depth Sensor Simulator

SimSense is a GPU-accelerated depth sensor simulator for python, implemented with CUDA. Based on semi-global matching, SimSense encapsulated various algorithms to compute depth from a pair of stereo images. It can achieve over 250 FPS whereas usual CPU implementations can hardly achieve 1 fps. This library has been integrated into the open-source simulation environment SAPIEN.

NeRF on Bottles

This is the final project for my course CSE 291: Machine Learning for 3D Geometry at UCSD, in which I reproduced Neural Radiance Fields on the bottles dataset.

Simple MVS

A Multi-Vew Stereo reconstruction pipeline implemented with OpenCV and Open3D. I designed this pipeline to be used as the final assignment for the class CSE 152A: Introduction to Computer Vision of Fall 2021 at UCSD.


Instructional Assistant for CSE 152A: Introduction to Computer Vision of 2022 Fall at UCSD. Instructor: Manmohan Chandraker

Modified from Jon Barron's personal website.