Kelvin Wong
Kelvin is a research scientist at Uber ATG R&D. 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.
Recent Publications
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 (ECCV 2020)
LidarSIM: Realistic LiDAR Simulation by Leveraging the Real World
Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun (CVPR 2020, oral)
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun (CVPR 2020, oral)
Identifying Unknown Instances for Autonomous Driving
Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun (CoRL 2019)