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Wenjie Luo

Wenjie is a Senior Research Scientist and a founding member of the Uber ATG R&D team. His research interests include computer vision and machine learning, and his work spans the full autonomy stack including perception, prediction, and planning. Previously, he earned his master’s at TTI-Chicago and continued to the PhD program at the University of Toronto, both under Professor Raquel Urtasun. Wenjie also spent some time at Apple SPG before joining Uber.

Recent publications

End-to-End Interpretable Neural Motion Planner

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

IntentNet: Learning to Predict Intention from Raw Sensor Data

Sergio Casas, Wenjie Luo, Raquel Urtasun (CORL 2018, spotlight)

Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds

Chris Zhang, Wenjie Luo, Raquel Urtasun (3DV 2018, spotlight)

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)

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

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

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)

DeepRoadMapper: Extracting Road Topology from Aerial Images

Gellért Máttyus, Wenjie Luo, Raquel Urtasun (ICCV 2017)