- I am currently an applied scientist at Amazon AWS.
- I was a PhD student at the University of Toronto in the Machine Learning and Computer Vision group since January 2017, supervised by Prof. Raquel Urtasun. Additionally, I was part of the Uber Advanced Technologies Group in Toronto, also led by Prof. Raquel Urtasun, from May 2017 to February 2021.
- Before this, I obtained my MSc. in Computer Science in the same group.
- My research interests include computer vision and various related machine learning techniques.
- I completed an undergraduate degree in 2013 at the University of Waterloo in Electrical Engineering with a focus on high frequency circuits, electromagnetism, and communication systems.
- My CV is available here.
- Implicit Surface Contrastive Clustering for LiDAR Point Clouds
Zaiwei Zhang, Min Bai, Erran Li
To appear in Computer Vision and Pattern Recognition (CVPR) 2023
- Improving Self-Supervised Representation Learning via Sequential Adversarial Masking
Dylan Sam, Min Bai, Tristan J. McKinney, Li Erran Li
In NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice, 2022
- Self-Supervised Pretraining for Large-Scale Point Clouds
Zaiwei Zhang, Min Bai, Erran Li
In Neural Information Processing Systems (NeurIPS) 2022
- Auto4D: Learning to Label 4D Objects from Sequential Point Clouds
Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, Raquel Urtasun
Submitted to International Conference on Intelligent Robotics and Systems (IROS) 2021
- Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving
Min Bai, Shenlong Wang, Kelvin Wong, Ersin Yumer, Raquel Urtasun
In Arxiv preprint, arXiv:2101.06865, Jan 2021
- Exploiting Sparse Semantic HD Maps for Affordable Localization
Wei-Chiu Ma*, Ignacio Tartavull*, Ioan Andrei Barsan*, Shenlong Wang*, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
In International Conference on Intelligent Robotics and Systems (IROS) 2019
- UPSNet: A Unified Panoptic Segmentation Network
Yuwen Xiong*, Renjie Liao*, Hengshuang Zhao*, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun
In Computer Vision and Pattern Recognition (CVPR) 2019
- Deep Multi-Sensor Lane Detection
Min Bai*, Gellert Mattyus*, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
In International Conference on Intelligent Robotics and Systems (IROS) 2018
- Learning Deep Structured Active Contours End-to-End
Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun
In Computer Vision and Pattern Recognition (CVPR) 2018
- TorontoCity: Seeing the World with a Million Eyes
Shenlong Wang, Min Bai*, Gellert Mattyus*, Hang Chu*, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun.
In International Conference on Computer Vision (ICCV) 2017 (spotlight)
- Deep Watershed Transform for Instance Segmentation
Min Bai, Raquel Urtasun.
In Computer Vision and Pattern Recognition (CVPR) 2017
- Exploiting Semantic Information and Deep Matching for Optical Flow
Min Bai*, Wenjie Luo*, Kaustav Kundu, and Raquel Urtasun. (* denotes equal contribution)
In European Conference on Computer Vision (ECCV) 2016
Prior work experience
- From 2013-2015, I was a Wireless Systems Engineer at Apple Inc in Cupertino, California.
- During my undergrad, I completed various internships (mostly in electronics and electrical systems related fields) at NVIDIA Corporation, BlackBerry Limited, Independent Electricity Systems Operator of Ontario, and Genesys Telecommunications.
mbai (at) cs (dot) toronto (dot) edu