Kelvin Wong
Kelvin is a research scientist at Uber ATG Toronto. He is also a graduate student at the University of Toronto, where he is supervised by Professor Raquel Urtasun. His research interests include machine learning, computer vision, and their applications to autonomous vehicles.
Research Papers
Identifying Unknown Instances for Autonomous Driving
K. Wong, S. Wang, M. Ren, M. Liang, R. Urtasun
We propose a novel open-set instance segmentation algorithm for point clouds that identifies instances from both known and unknown classes. In particular, we train a deep convolutional neural network that projects points belonging to the same instance together in a category-agnostic embedding space. [PDF]
The Conference on Robot Learning (CoRL), 2019
We propose a novel open-set instance segmentation algorithm for point clouds that identifies instances from both known and unknown classes. In particular, we train a deep convolutional neural network that projects points belonging to the same instance together in a category-agnostic embedding space. [PDF]
The Conference on Robot Learning (CoRL), 2019