Hello! I am a researcher in robotic 3D perception. My goal is to create algorithms that build scene representations in new environments with brief observations and interactions in a short period of time, so as to enable fast and scalable autonomy deployment. The tools I leverage to work towards this goal mainly include symmetry-aware geometric deep learning, physics-informed multimodal perception, and data-based prior from foundation models.
I am currently an Assistant Research Scientist at the University of Michigan CURLY lab, advised by Maani Ghaffari, and a Postdoctoral Researcher at the University of Pennsylvania DAIR lab, advised by Michael Posa. I obtained my Ph. D. in Mechanical Engineering from the University of Michigan, under the supervision of Huei Peng and Maani Ghaffari.
Please check out my Google Scholar page for the full list of my publications.
Selected Publications
SE3ET: SE(3)-Equivariant Transformer for Low-Overlap Point Cloud Registration
Chien Erh Lin, Minghan Zhu, Maani Ghaffari
IEEE Robotics and Automation Letters, 2024
Paper | Code
Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras
Tzu-Yuan Lin*, Minghan Zhu*, Maani Ghaffari
International Conference on Machine Learning (ICML), 2024
Paper | Code
4D Panoptic Segmentation as Invariant and Equivariant Field Prediction
Minghan Zhu, Shizhong Han, Hong Cai, Shubhankar Borse, Maani Ghaffari, Fatih Porikli
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
Paper | Code | Project
E2PN: Efficient SE(3)-Equivariant Point Network
Minghan Zhu, Maani Ghaffari, William A Clark, Huei Peng
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Paper | Code
MonoEdge: Monocular 3D Object Detection Using Local Perspectives
Minghan Zhu, Lingting Ge, Panqu Wang, Huei Peng
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023
Paper
SE(3)-Equivariant Point Cloud-Based Place Recognition
Chien Erh Lin, Jingwei Song, Ray Zhang, Minghan Zhu, Maani Ghaffari
Conference on Robot Learning (CoRL), 2022,
Paper | Code
Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations
Minghan Zhu, Maani Ghaffari, Huei Peng
Conference on Robot Learning (CoRL), 2021,
Paper | Code
Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
Minghan Zhu, Songan Zhang, Yuanxin Zhong, Pingping Lu, Huei Peng, John Lenneman
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
Paper | Code
Monocular Depth Prediction through Continuous 3D Loss
Minghan Zhu, Maani Ghaffari, Yuanxin Zhong, Pingping Lu, Zhong Cao, Ryan M Eustice, Huei Peng
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Paper | Code
