My research is related to 3D scene understanding, camera calibration and robotics.
I was previously a Master student in Robotics. Before that, I received my B.S.E. degrees in Computer Science at UM and Mechanical Engineering at Shanghai Jiao Tong University through a dual degree program at UM-SJTU Joint Institute.
I am looking for internship position in 2024. Please feel free to contact me if you think I’d be a good match!
- [2023/09] I will be a visiting student at since David is moving there!
- [2023/06] We have released demo for PerspectiveFields. Try it out on your camera calibration problem!
- [2023/03] Perspective Fields for Single Image Camera Calibration is selected as a highlight!
- [2023/02] Two papers are accepted at CVPR 2023!
Learning 3D implicit function from a single input image. Unlike other methods, D2-DRDF does not depend on mesh supervision during training and can directly operate with raw RGB-D data obtained from scene captures.
We introduce a simpler approach that uses a transformer applied to 3D-aware plane tokens to perform 3D reasoning. This is substantially more effective than SparsePlanes.
We learn to reconstruct scenes from sparse views with an unknown relationship. We take advantage of planar regions and their geometric properties to recover the scene layout.
We augment a manipulation planner for cluttered environments with a shape completion network and a volumetric memory system, allowing the robot to reason about what may be contained in occluded areas.