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ATG R&D Publications

Cutting-edge self-driving vehicle research in computer vision, machine learning, and robotics published in top conferences and journals by the Uber ATG R&D team.

Importance of Prior Knowledge in Precise Multimodal Prediction

Sergio Casas*, Cole Gulino*, Simon Suo*, and Raquel Urtasun (IROS 2020, oral)

Multi-Agent Routing Value Iteration Network

Quinlan Sykora, Mengye Ren, Raquel Urtasun (ICML 2020)

Hierarchical Verification for Adversarial Robustness

Cong Han Lim, Raquel Urtasun, Ersin Yumer (ICML 2020)

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun (ECCV 2020)

DSDNet: Deep Structured self-Driving Network

Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun (ECCV 2020)

Dense RepPoints: Representing Visual Objects with Dense Point Sets

Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu (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)

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)

Conditional Entropy Coding for Efficient Video Compression

Jerry Liu, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun (ECCV 2020)

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)

Weakly-supervised 3D Shape Completion in the Wild

Jiayuan Gu, Wei-Chiu Ma, Siva Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, and Raquel Urtasun (ECCV 2020)

Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations

Abbas Sadat*, Sergio Casas*, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun (ECCV 2020)

LevelSet R-CNN: A Deep Variational Method for Instance Segmentation

Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, 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)

PolyTransform: Deep Polygon Transformer for Instance Segmentation

Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun (CVPR 2020)

OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression

Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun (CVPR 2020, oral)

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)

Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles

Abbas Sadat*, Mengye Ren*, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun (IROS 2019, oral)

Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization

Wei-Chiu Ma*, Ignacio Tartavull*, Ioan Andrei Barsan*, Shenlong Wang*, Min Bai, Gellert Mattyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun (IROS 2019)

Identifying Unknown Instances for Autonomous Driving

Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun (CoRL 2019)

DSIC: Deep Stereo Image Compression

Jerry Liu, Shenlong Wang, Raquel Urtasun (ICCV 2019, oral)

Learning Joint 2D-3D Representations for Depth Completion

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

DAGMapper: Learning to Map by Discovering Lane Topology

Namdar Homayounfar, Wei-Chiu Ma*, Justin Liang*, Xinyu Wu, Jack Fan, Raquel Urtasun (ICCV 2019)

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch

Shivam Duggal, Shenlong Wang, Wei-Chiu Ma, Rui Hu, 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)

UPSNet: A Unified Panoptic Segmentation Network

Yuwen Xiong*, Renjie Liao*, Hengshuang Zhao*, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun (CVPR 2019, oral)

Convolutional Recurrent Network for Road Boundary Extraction

Justin Liang*, Namdar Homayounfar*, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun (CVPR 2019)

Learning to Localize Through Compressed Binary Maps

Xinkai Wei*, Ioan Andrei Bârsan*, Shenlong Wang*, Julieta Martinez, Raquel Urtasun (CVPR 2019)

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

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

Deep Rigid Instance Scene Flow

Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, Raquel Urtasun (CVPR 2019)

DeepSignals: Predicting Intent of Drivers Through Visual Signals

Davi Frossard, Eric Kee, Raquel Urtasun (ICRA 2019)

Graph HyperNetworks for Neural Architecture Search

Chris Zhang, Mengye Ren, Raquel Urtasun (ICLR 2019)

Deep Multi-Sensor Lane Detection

Min Bai*, Gellért Máttyus*, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun (IROS 2018, oral)

HDNET: Exploiting HD Maps for 3D Object Detection

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

IntentNet: Learning to Predict Intention from Raw Sensor Data

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

Learning to Localize Using a LiDAR Intensity Map

Ioan Andrei Bârsan*, Shenlong Wang*, Andrei Pokrovsky, 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)

Deep Continuous Fusion for Multi-Sensor 3D Object Detection

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

End-to-End Deep Structured Models for Drawing Crosswalks

Justin Liang, 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)

Deep Parametric Continuous Convolutional Neural Networks

Shenlong Wang*, Simon Suo*, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun (CVPR 2018, spotlight)

Hierarchical Recurrent Attention Networks for Structured Online Maps

Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun (CVPR 2018)

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

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

Matching Adversarial Networks

Gellért Máttyus, Raquel Urtasun (CVPR 2018)

Learning to Reweight Examples for Robust Deep Learning

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

End-to-End Learning of Multi-Sensor 3D Tracking by Detection

Davi Frossard, Raquel Urtasun (ICRA 2018)

DeepRoadMapper: Extracting Road Topology From Aerial Images

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

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