Kelvin Wong

I am a PhD student at the University of Toronto and the Vector Institute, where I work on machine learning and self-driving cars. My advisor is Raquel Urtasun.

Previously, I was a research scientist at Uber Advanced Technologies Group. I earned my MSc from the University of Toronto, my BCS from the University of Waterloo, and my BBA from Wilfrid Laurier University. During my undergrad, I was fortunate to have worked with Will Evans and Peter van Beek.

Email / Google Scholar / LinkedIn / Twitter

Research
	SceneGen: Learning to Generate Realistic Traffic Scenes Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun Computer Vision and Pattern Recognition (CVPR), 2021 An autoregressive model of traffic scenes.
	Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving Min Bai, Shenlong Wang, Kelvin Wong, Ersin Yumer, Raquel Urtasun arXiv, 2021 Spatio-temporal segmentation of construction zones.
	MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models Sourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun Neural Information Processing Systems (NeurIPS), 2020 Multi-sweep LiDAR compression using deep entropy models.
	Simultaneous Visibility Representations of Undirected Pairs of Graphs Ben Chugg, Will Evans, Kelvin Wong Computational Geometry: Theory and Applications, 2021 Canadian Conference on Computational Geometry (CCCG), 2020 Visualize pairs of undirected graphs simulatenously.
	Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun European Conference on Computer Vision (ECCV), 2020 Test motion planning using simulated perception and prediction outputs.
	OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun Computer Vision and Pattern Recognition (CVPR), 2020 (Oral) Single-sweep LiDAR compression using deep entropy models.
	LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Wei-Chiu Ma, Raquel Urtasun Computer Vision and Pattern Recognition (CVPR), 2020 (Oral) Realistic LiDAR simulation for self-driving vehicles.
	Deformable Filter Convolution for Point Cloud Reasoning Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun NeurIPS Workshop on Sets and Partitions, 2019 Deformable convolution for 3D point clouds.
	Identifying Unknown Instances for Autonomous Driving Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun Conference on Robot Learning (CoRL), 2019 (Spotlight) 3D perception for the open-set world.

Service

Conference Reviewer: AAAI 2021, CVPR 2021

Website shamelessly copied from Jon Barron.