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Bin Yang

Bin is a Senior Research Scientist at Uber ATG R&D. He is also a PhD student at the University of Toronto, supervised by Professor Raquel Urtasun. Bin’s research interest lies in computer vision and deep learning, with a focus on 3D perception in an autonomous driving scenario.

Recent publications

Learning Lane Graph Representations for Motion Forecasting

Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun (ECCV 2020, oral)

RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects

Bin Yang*, Runsheng Guo*, Ming Liang, Sergio Casas, Raquel Urtasun (ECCV 2020)

V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction

Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, Raquel Urtasun (ECCV 2020, oral)

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)

End-to-end Contextual Perception and Prediction with Interaction Transformer

Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun (ECCV 2020, oral)

DSDNet: Deep Structured self-Driving Network

Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, 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)

Physically Realizable Adversarial Examples for LiDAR Detection

James Tu, Mengye Ren, Siva Manivasagam, Bin Yang, Ming Liang, Richard Du, Frank Cheng, Raquel Urtasun (CVPR 2020)

PnPNet: End-to-End Perception and Prediction with Tracking in the Loop

Ming Liang*, Bin Yang*, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, Raquel Urtasun (CVPR 2020)

Learning Joint 2D-3D Representations for Depth Completion

Yun Chen*, Bin Yang*, Ming Liang, Raquel Urtasun (ICCV 2019)

End-to-End Interpretable Neural Motion Planner

Wenyuan Zeng*, Wenjie Luo*, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun (CVPR 2019, oral)

Multi-Task Multi-Sensor Fusion for 3D Object Detection

Ming Liang*, Bin Yang*, Yun Chen, Rui Hu, Raquel Urtasun (CVPR 2019)

HDNET: Exploiting HD Maps for 3D Object Detection

Bin Yang, Ming Liang, Raquel Urtasun (CORL 2018, spotlight)

Deep Continuous Fusion for Multi-Sensor 3D Object Detection

Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun (ECCV 2018)

Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

Wenjie Luo, Bin Yang, Raquel Urtasun (CVPR 2018, oral)

SBNet: Sparse Blocks Network for Fast Inference

Mengye Ren*, Andrei Pokrovsky*, Bin Yang*, Raquel Urtasun (CVPR 2018, spotlight)

PIXOR: Real-Time 3D Object Detection from Point Clouds

Bin Yang, Wenjie Luo, Raquel Urtasun (CVPR 2018)

Learning to Reweight Examples for Robust Deep Learning

Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun (ICML 2018, spotlight)

TorontoCity: Seeing the World With a Million Eyes

Shenlong Wang, Min Bai, Gellért Máttyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun (ICCV 2017, spotlight)