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)
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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