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Raquel Urtasun
Person information
- affiliation: University of Toronto, Canada
- affiliation: Waabi
- affiliation (former): Swiss Federal Institute of Technology in Lausanne, Switzerland
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2020 – today
- 2024
- [c242]Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun:
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion. ICLR 2024 - [c241]Sourav Biswas, Sergio Casas, Quinlan Sykora, Ben Agro, Abbas Sadat, Raquel Urtasun:
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving. ICRA 2024: 14236-14243 - [c240]Jack Lu, Kelvin Wong, Chris Zhang, Simon Suo, Raquel Urtasun:
SceneControl: Diffusion for Controllable Traffic Scene Generation. ICRA 2024: 16908-16914 - [i155]Sourav Biswas, Sergio Casas, Quinlan Sykora, Ben Agro, Abbas Sadat, Raquel Urtasun:
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving. CoRR abs/2404.01486 (2024) - [i154]Sergio Casas, Ben Agro, Jiageng Mao, Thomas Gilles, Alexander Cui, Thomas Li, Raquel Urtasun:
DeTra: A Unified Model for Object Detection and Trajectory Forecasting. CoRR abs/2406.04426 (2024) - [i153]Ben Agro, Quinlan Sykora, Sergio Casas, Thomas Gilles, Raquel Urtasun:
UnO: Unsupervised Occupancy Fields for Perception and Forecasting. CoRR abs/2406.08691 (2024) - 2023
- [c239]Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun:
Learning Realistic Traffic Agents in Closed-loop. CoRL 2023: 800-821 - [c238]Jay Sarva, Jingkang Wang, James Tu, Yuwen Xiong, Sivabalan Manivasagam, Raquel Urtasun:
Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation. CoRL 2023: 1316-1334 - [c237]Ali Athar, Enxu Li, Sergio Casas, Raquel Urtasun:
4D-Former: Multimodal 4D Panoptic Segmentation. CoRL 2023: 2151-2164 - [c236]James Tu, Simon Suo, Chris Zhang, Kelvin Wong, Raquel Urtasun:
Towards Scalable Coverage-Based Testing of Autonomous Vehicles. CoRL 2023: 2611-2623 - [c235]Anqi Joyce Yang, Sergio Casas, Nikita Dvornik, Sean Segal, Yuwen Xiong, Jordan Sir Kwang Hu, Carter Fang, Raquel Urtasun:
LabelFormer: Object Trajectory Refinement for Offboard Perception from LiDAR Point Clouds. CoRL 2023: 3364-3383 - [c234]Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun:
Learning Compact Representations for LiDAR Completion and Generation. CVPR 2023: 1074-1083 - [c233]Ben Agro, Quinlan Sykora, Sergio Casas, Raquel Urtasun:
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving. CVPR 2023: 1379-1388 - [c232]Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun:
UniSim: A Neural Closed-Loop Sensor Simulator. CVPR 2023: 1389-1399 - [c231]Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection from LiDAR Point Clouds. CVPR 2023: 9317-9328 - [c230]Simon Suo, Kelvin Wong, Justin Xu, James Tu, Alexander Cui, Sergio Casas, Raquel Urtasun:
MIXSIM: A Hierarchical Framework for Mixed Reality Traffic Simulation. CVPR 2023: 9622-9631 - [c229]Enxu Li, Sergio Casas, Raquel Urtasun:
MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory. ICCV 2023: 745-754 - [c228]Sivabalan Manivasagam, Ioan Andrei Bârsan, Jingkang Wang, Ze Yang, Raquel Urtasun:
Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing. ICCV 2023: 8238-8248 - [c227]Jeffrey Yunfan Liu, Yun Chen, Ze Yang, Jingkang Wang, Sivabalan Manivasagam, Raquel Urtasun:
Real-Time Neural Rasterization for Large Scenes. ICCV 2023: 8382-8393 - [c226]Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo, Raquel Urtasun:
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting. ICRA 2023: 7801-7807 - [c225]Ze Yang
, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun:
Reconstructing Objects in-the-wild for Realistic Sensor Simulation. ICRA 2023: 11661-11668 - [c224]Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun:
Neural Lighting Simulation for Urban Scenes. NeurIPS 2023 - [i152]Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-loop Training for Autonomous Driving. CoRR abs/2306.15713 (2023) - [i151]Ben Agro, Quinlan Sykora, Sergio Casas, Raquel Urtasun:
Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving. CoRR abs/2308.01471 (2023) - [i150]Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, Raquel Urtasun:
UniSim: A Neural Closed-Loop Sensor Simulator. CoRR abs/2308.01898 (2023) - [i149]Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun:
Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion. CoRR abs/2311.01017 (2023) - [i148]Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun:
Learning Realistic Traffic Agents in Closed-loop. CoRR abs/2311.01394 (2023) - [i147]Anqi Joyce Yang, Sergio Casas, Nikita Dvornik, Sean Segal, Yuwen Xiong, Jordan Sir Kwang Hu, Carter Fang, Raquel Urtasun:
LabelFormer: Object Trajectory Refinement for Offboard Perception from LiDAR Point Clouds. CoRR abs/2311.01444 (2023) - [i146]Jay Sarva, Jingkang Wang, James Tu, Yuwen Xiong, Sivabalan Manivasagam, Raquel Urtasun:
Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation. CoRR abs/2311.01446 (2023) - [i145]Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Bârsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun:
CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation. CoRR abs/2311.01447 (2023) - [i144]Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, Raquel Urtasun:
UltraLiDAR: Learning Compact Representations for LiDAR Completion and Generation. CoRR abs/2311.01448 (2023) - [i143]Ali Athar, Enxu Li, Sergio Casas, Raquel Urtasun:
4D-Former: Multimodal 4D Panoptic Segmentation. CoRR abs/2311.01520 (2023) - [i142]Enxu Li, Sergio Casas, Raquel Urtasun:
MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory. CoRR abs/2311.01556 (2023) - [i141]Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection From LiDAR Point Clouds. CoRR abs/2311.02007 (2023) - [i140]Ze Yang, Sivabalan Manivasagam, Yun Chen, Jingkang Wang, Rui Hu, Raquel Urtasun:
Reconstructing Objects in-the-wild for Realistic Sensor Simulation. CoRR abs/2311.05602 (2023) - [i139]Jeffrey Yunfan Liu, Yun Chen, Ze Yang, Jingkang Wang, Sivabalan Manivasagam, Raquel Urtasun:
Real-Time Neural Rasterization for Large Scenes. CoRR abs/2311.05607 (2023) - [i138]Ava Pun, Gary Sun, Jingkang Wang, Yun Chen, Ze Yang, Sivabalan Manivasagam, Wei-Chiu Ma, Raquel Urtasun:
LightSim: Neural Lighting Simulation for Urban Scenes. CoRR abs/2312.06654 (2023) - 2022
- [j15]Xiaojuan Qi
, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia
:
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 969-984 (2022) - [c223]Jingkang Wang, Sivabalan Manivasagam, Yun Chen, Ze Yang, Ioan Andrei Barsan, Anqi Joyce Yang, Wei-Chiu Ma, Raquel Urtasun:
CADSim: Robust and Scalable in-the-wild 3D Reconstruction for Controllable Sensor Simulation. CoRL 2022: 630-642 - [c222]Wei-Chiu Ma, Anqi Joyce Yang, Shenlong Wang, Raquel Urtasun, Antonio Torralba:
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry. CVPR 2022: 15903-15913 - [c221]Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-Loop Training for Autonomous Driving. ECCV (39) 2022: 264-282 - [c220]Shivam Duggal, Zihao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun:
Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild. WACV 2022: 277-286 - [i137]Wei-Chiu Ma, Anqi Joyce Yang, Shenlong Wang, Raquel Urtasun, Antonio Torralba:
Virtual Correspondence: Humans as a Cue for Extreme-View Geometry. CoRR abs/2206.08365 (2022) - [i136]Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo, Raquel Urtasun:
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting. CoRR abs/2211.02545 (2022) - 2021
- [c219]Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes. CoRL 2021: 816-826 - [c218]James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-sensor Perception Systems in Self Driving. CoRL 2021: 1013-1024 - [c217]Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning To Generate Realistic Traffic Scenes. CVPR 2021: 892-901 - [c216]John Phillips, Julieta Martinez, Ioan Andrei Barsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CVPR 2021: 4679-4689 - [c215]Yun Chen, Frieda Rong, Shivam Duggal, Shenlong Wang, Xinchen Yan, Sivabalan Manivasagam, Shangjie Xue, Ersin Yumer, Raquel Urtasun:
GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving. CVPR 2021: 7230-7240 - [c214]Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CVPR 2021: 9909-9918 - [c213]Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun:
TrafficSim: Learning To Simulate Realistic Multi-Agent Behaviors. CVPR 2021: 10400-10409 - [c212]Ze Yang
, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun:
S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling. CVPR 2021: 13284-13293 - [c211]Sergio Casas, Abbas Sadat, Raquel Urtasun:
MP3: A Unified Model To Map, Perceive, Predict and Plan. CVPR 2021: 14403-14412 - [c210]Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Barsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks. CVPR 2021: 15699-15708 - [c209]James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. ICCV 2021: 7748-7757 - [c208]Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun Waabi:
Self-Supervised Representation Learning from Flow Equivariance. ICCV 2021: 10171-10180 - [c207]Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, Raquel Urtasun:
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. ICCV 2021: 16087-16096 - [c206]Renjie Liao, Raquel Urtasun, Richard S. Zemel:
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. ICLR 2021 - [c205]Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. ICRA 2021: 4875-4881 - [c204]Jerry Liu, Wenyuan Zeng, Raquel Urtasun, Ersin Yumer:
Deep Structured Reactive Planning. ICRA 2021: 4897-4904 - [c203]Anqi Joyce Yang, Can Cui, Ioan Andrei Bârsan, Raquel Urtasun, Shenlong Wang:
Asynchronous Multi-View SLAM. ICRA 2021: 5669-5676 - [c202]Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun:
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. IROS 2021: 532-539 - [c201]Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun:
Safety-Oriented Pedestrian Occupancy Forecasting. IROS 2021: 1015-1022 - [c200]Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun:
PLUMENet: Efficient 3D Object Detection from Stereo Images. IROS 2021: 3383-3390 - [c199]Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer:
Diverse Complexity Measures for Dataset Curation in Self-Driving. IROS 2021: 8609-8616 - [c198]Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao:
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation. UAI 2021: 1089-1099 - [i135]Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun:
Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting. CoRR abs/2101.02385 (2021) - [i134]Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning to Generate Realistic Traffic Scenes. CoRR abs/2101.06541 (2021) - [i133]Yun Chen, Frieda Rong, Shivam Duggal, Shenlong Wang, Xinchen Yan, Sivabalan Manivasagam, Shangjie Xue, Ersin Yumer, Raquel Urtasun:
GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition. CoRR abs/2101.06543 (2021) - [i132]Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
VideoClick: Video Object Segmentation with a Single Click. CoRR abs/2101.06545 (2021) - [i131]Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, Raquel Urtasun:
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. CoRR abs/2101.06547 (2021) - [i130]Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CoRR abs/2101.06549 (2021) - [i129]Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun:
Self-Supervised Representation Learning from Flow Equivariance. CoRR abs/2101.06553 (2021) - [i128]Abbas Sadat, Sean Segal, Sergio Casas, James Tu, Bin Yang, Raquel Urtasun, Ersin Yumer:
Diverse Complexity Measures for Dataset Curation in Self-driving. CoRR abs/2101.06554 (2021) - [i127]Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun:
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors. CoRR abs/2101.06557 (2021) - [i126]James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. CoRR abs/2101.06560 (2021) - [i125]Anqi Joyce Yang, Can Cui, Ioan Andrei Bârsan, Raquel Urtasun, Shenlong Wang:
Asynchronous Multi-View SLAM. CoRR abs/2101.06562 (2021) - [i124]Ze Yang, Shenlong Wang, Sivabalan Manivasagam, Zeng Huang, Wei-Chiu Ma, Xinchen Yan, Ersin Yumer, Raquel Urtasun:
S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling. CoRR abs/2101.06571 (2021) - [i123]Bin Yang, Min Bai, Ming Liang, Wenyuan Zeng, Raquel Urtasun:
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds. CoRR abs/2101.06586 (2021) - [i122]Jingkang Wang, Mengye Ren, Ilija Bogunovic, Yuwen Xiong, Raquel Urtasun:
Cost-Efficient Online Hyperparameter Optimization. CoRR abs/2101.06590 (2021) - [i121]Yan Wang, Bin Yang, Rui Hu, Ming Liang, Raquel Urtasun:
PLUME: Efficient 3D Object Detection from Stereo Images. CoRR abs/2101.06594 (2021) - [i120]Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun:
Network Automatic Pruning: Start NAP and Take a Nap. CoRR abs/2101.06608 (2021) - [i119]Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun:
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. CoRR abs/2101.06653 (2021) - [i118]Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun:
End-to-end Interpretable Neural Motion Planner. CoRR abs/2101.06679 (2021) - [i117]John Phillips, Julieta Martinez, Ioan Andrei Bârsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CoRR abs/2101.06720 (2021) - [i116]Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun:
Deep Parametric Continuous Convolutional Neural Networks. CoRR abs/2101.06742 (2021) - [i115]James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving. CoRR abs/2101.06784 (2021) - [i114]Sergio Casas, Abbas Sadat, Raquel Urtasun:
MP3: A Unified Model to Map, Perceive, Predict and Plan. CoRR abs/2101.06806 (2021) - [i113]Jerry Liu
, Wenyuan Zeng, Raquel Urtasun, Ersin Yumer:
Deep Structured Reactive Planning. CoRR abs/2101.06832 (2021) - [i112]Shivam Duggal, Zihao Wang, Wei-Chiu Ma, Sivabalan Manivasagam, Justin Liang, Shenlong Wang, Raquel Urtasun:
Secrets of 3D Implicit Object Shape Reconstruction in the Wild. CoRR abs/2101.06860 (2021) - [i111]Min Bai, Shenlong Wang, Kelvin Wong, Ersin Yumer, Raquel Urtasun:
Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving. CoRR abs/2101.06865 (2021) - [i110]Wei-Chiu Ma, Shenlong Wang, Jiayuan Gu, Sivabalan Manivasagam, Antonio Torralba, Raquel Urtasun:
Deep Feedback Inverse Problem Solver. CoRR abs/2101.07719 (2021) - [i109]Sergio Casas, Wenjie Luo, Raquel Urtasun:
IntentNet: Learning to Predict Intention from Raw Sensor Data. CoRR abs/2101.07907 (2021) - [i108]Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes. CoRR abs/2104.03956 (2021) - [i107]Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao:
NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation. CoRR abs/2106.13435 (2021) - 2020
- [c197]Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sida Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun:
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion. CoRL 2020: 31-48 - [c196]Ze Yang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
Recovering and Simulating Pedestrians in the Wild. CoRL 2020: 419-431 - [c195]Sean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun:
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs. CoRL 2020: 973-983 - [c194]Davi Frossard, Shun Da Suo, Sergio Casas, James Tu, Raquel Urtasun:
StrObe: Streaming Object Detection from LiDAR Packets. CoRL 2020: 1174-1183 - [c193]Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRL 2020: 1195-1210 - [c192]Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu, Raquel Urtasun:
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression. CVPR 2020: 1310-1320 - [c191]Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun:
PolyTransform: Deep Polygon Transformer for Instance Segmentation. CVPR 2020: 9128-9137 - [c190]Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World. CVPR 2020: 11164-11173 - [c189]Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, Raquel Urtasun:
PnPNet: End-to-End Perception and Prediction With Tracking in the Loop. CVPR 2020: 11550-11559 - [c188]James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CVPR 2020: 13713-13722 - [c187]Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun:
DSDNet: Deep Structured Self-driving Network. ECCV (21) 2020: 156-172 - [c186]Ze Yang
, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. ECCV (21) 2020: 227-244 - [c185]Wei-Chiu Ma, Shenlong Wang, Jiayuan Gu, Sivabalan Manivasagam, Antonio Torralba, Raquel Urtasun:
Deep Feedback Inverse Problem Solver. ECCV (5) 2020: 229-246 - [c184]Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, Raquel Urtasun:
Weakly-Supervised 3D Shape Completion in the Wild. ECCV (5) 2020: 283-299 - [c183]Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun:
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. ECCV (26) 2020: 312-329 - [c182]Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. ECCV (23) 2020: 414-430 - [c181]Jerry Liu, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun:
Conditional Entropy Coding for Efficient Video Compression. ECCV (17) 2020: 453-468 - [c180]Bin Yang, Runsheng Guo, Ming Liang, Sergio Casas, Raquel Urtasun:
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects. ECCV (18) 2020: 496-512 - [c179]Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun:
Learning Lane Graph Representations for Motion Forecasting. ECCV (2) 2020: 541-556 - [c178]Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation. ECCV (23) 2020: 555-571 - [c177]Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, Raquel Urtasun:
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction. ECCV (2) 2020: 605-621 - [c176]Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun:
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. ECCV (23) 2020: 624-641 - [c175]Cong Han Lim, Raquel Urtasun, Ersin Yumer:
Hierarchical Verification for Adversarial Robustness. ICML 2020: 6072-6082 - [c174]Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. ICML 2020: 9300-9310 - [c173]Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun:
SpAGNN: Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. ICRA 2020: 9491-9497 - [c172]Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun:
The Importance of Prior Knowledge in Precise Multimodal Prediction. IROS 2020: 2295-2302 - [c171]Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. IROS 2020: 4477-4484 - [c170]Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. IROS 2020: 5784-5791 - [c169]Sourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun:
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models. NeurIPS 2020 - [c168]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. NeurIPS 2020 - [i106]James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CoRR abs/2004.00543 (2020) - [i105]Lila Huang, Shenlong Wang, Kelvin Wong, Jerry Liu
, Raquel Urtasun:
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression. CoRR abs/2005.07178 (2020) - [i104]Kibok Lee, Zhuoyuan Chen, Xinchen Yan, Raquel Urtasun, Ersin Yumer:
ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds. CoRR abs/2005.11626 (2020) - [i103]Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, Raquel Urtasun:
PnPNet: End-to-End Perception and Prediction with Tracking in the Loop. CoRR abs/2005.14711 (2020) - [i102]Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun:
The Importance of Prior Knowledge in Precise Multimodal Prediction. CoRR abs/2006.02636 (2020) - [i101]Sivabalan Manivasagam, Shenlong Wang, Kelvin Wong, Wenyuan Zeng, Mikita Sazanovich, Shuhan Tan, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World. CoRR abs/2006.09348 (2020) - [i100]Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. CoRR abs/2007.05096 (2020) - [i99]Cong Han Lim, Raquel Urtasun, Ersin Yumer:
Hierarchical Verification for Adversarial Robustness. CoRR abs/2007.11826 (2020) - [i98]Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun:
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. CoRR abs/2007.12036 (2020) - [i97]Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun:
Learning Lane Graph Representations for Motion Forecasting. CoRR abs/2007.13732 (2020) - [i96]Bin Yang, Runsheng Guo, Ming Liang, Sergio Casas, Raquel Urtasun:
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects. CoRR abs/2007.14366 (2020) - [i95]Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun:
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation. CoRR abs/2007.15629 (2020) - [i94]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. CoRR abs/2008.01342 (2020) - [i93]Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. CoRR abs/2008.05927 (2020) - [i92]Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. CoRR abs/2008.05930 (2020) - [i91]Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun:
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction. CoRR abs/2008.06020 (2020) - [i90]Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun:
DSDNet: Deep Structured self-Driving Network. CoRR abs/2008.06041 (2020) - [i89]Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, James Tu, Raquel Urtasun:
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction. CoRR abs/2008.07519 (2020) - [i88]Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam, Wenyuan Zeng, Zihao Wang, Yuwen Xiong, Hao Su, Raquel Urtasun:
Weakly-supervised 3D Shape Completion in the Wild. CoRR abs/2008.09110 (2020) - [i87]Jerry Liu
, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun:
Conditional Entropy Coding for Efficient Video Compression. CoRR abs/2008.09180 (2020) - [i86]Meet Shah, Zhiling Huang, Ankit Laddha, Matthew Langford, Blake Barber, Sidney Zhang, Carlos Vallespi-Gonzalez, Raquel Urtasun:
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion. CoRR abs/2010.00731 (2020) - [i85]Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Bârsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks. CoRR abs/2010.15703 (2020) - [i84]Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. CoRR abs/2011.01153 (2020) - [i83]Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRR abs/2011.05289 (2020) - [i82]Sean Segal, Eric Kee, Wenjie Luo, Abbas Sadat, Ersin Yumer, Raquel Urtasun:
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs. CoRR abs/2011.06165 (2020) - [i81]Davi Frossard, Simon Suo, Sergio Casas, James Tu, Rui Hu, Raquel Urtasun:
StrObe: Streaming Object Detection from LiDAR Packets. CoRR abs/2011.06425 (2020) - [i80]Sourav Biswas, Jerry Liu
, Kelvin Wong, Shenlong Wang, Raquel Urtasun:
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models. CoRR abs/2011.07590 (2020) - [i79]Ze Yang, Siva Manivasagam, Ming Liang, Bin Yang, Wei-Chiu Ma, Raquel Urtasun:
Recovering and Simulating Pedestrians in the Wild. CoRR abs/2011.08106 (2020) - [i78]Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia:
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation. CoRR abs/2012.06980 (2020) - [i77]Renjie Liao, Raquel Urtasun, Richard S. Zemel:
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. CoRR abs/2012.07690 (2020) - [i76]Ioan Andrei Bârsan, Shenlong Wang, Andrei Pokrovsky, Raquel Urtasun:
Learning to Localize Using a LiDAR Intensity Map. CoRR abs/2012.10902 (2020) - [i75]Xinkai Wei, Ioan Andrei Bârsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CoRR abs/2012.10942 (2020) - [i74]Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun:
Deep Continuous Fusion for Multi-Sensor 3D Object Detection. CoRR abs/2012.10992 (2020) - [i73]Justin Liang, Raquel Urtasun:
End-to-End Deep Structured Models for Drawing Crosswalks. CoRR abs/2012.11585 (2020) - [i72]Bin Yang, Ming Liang, Raquel Urtasun:
HDNET: Exploiting HD Maps for 3D Object Detection. CoRR abs/2012.11704 (2020) - [i71]Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun:
Convolutional Recurrent Network for Road Boundary Extraction. CoRR abs/2012.12160 (2020) - [i70]Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Hierarchical Recurrent Attention Networks for Structured Online Maps. CoRR abs/2012.12314 (2020) - [i69]Namdar Homayounfar, Wei-Chiu Ma, Justin Liang, Xinyu Wu, Jack Fan, Raquel Urtasun:
DAGMapper: Learning to Map by Discovering Lane Topology. CoRR abs/2012.12377 (2020) - [i68]Wenjie Luo, Bin Yang, Raquel Urtasun:
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net. CoRR abs/2012.12395 (2020) - [i67]Ming Liang, Bin Yang, Yun Chen, Rui Hu, Raquel Urtasun:
Multi-Task Multi-Sensor Fusion for 3D Object Detection. CoRR abs/2012.12397 (2020) - [i66]Yun Chen, Bin Yang, Ming Liang, Raquel Urtasun:
Learning Joint 2D-3D Representations for Depth Completion. CoRR abs/2012.12402 (2020) - [i65]Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. CoRR abs/2012.12437 (2020)
2010 – 2019
- 2019
- [c167]KiJung Yoon
, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in Probabilistic Graphical Models by Graph Neural Networks. ACSSC 2019: 868-875 - [c166]Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRL 2019: 384-393 - [c165]Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun:
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRL 2019: 407-419 - [c164]Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, Raquel Urtasun:
Deep Rigid Instance Scene Flow. CVPR 2019: 3614-3622 - [c163]Ming Liang, Bin Yang, Yun Chen, Rui Hu, Raquel Urtasun:
Multi-Task Multi-Sensor Fusion for 3D Object Detection. CVPR 2019: 7345-7353 - [c162]Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun:
DARNet: Deep Active Ray Network for Building Segmentation. CVPR 2019: 7431-7439 - [c161]Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun:
End-To-End Interpretable Neural Motion Planner. CVPR 2019: 8660-8669 - [c160]Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai
, Ersin Yumer, Raquel Urtasun:
UPSNet: A Unified Panoptic Segmentation Network. CVPR 2019: 8818-8826 - [c159]Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Shenlong Wang, Raquel Urtasun:
Convolutional Recurrent Network for Road Boundary Extraction. CVPR 2019: 9512-9521 - [c158]Xinkai Wei, Ioan Andrei Barsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CVPR 2019: 10316-10324 - [c157]Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Jack Fan, Xinyu Wu, Raquel Urtasun:
DAGMapper: Learning to Map by Discovering Lane Topology. ICCV 2019: 2911-2920 - [c156]Jerry Liu, Shenlong Wang, Raquel Urtasun:
DSIC: Deep Stereo Image Compression. ICCV 2019: 3136-3145 - [c155]Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun:
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. ICCV 2019: 3928-3937 - [c154]Shivam Duggal, Shenlong Wang, Wei-Chiu Ma, Rui Hu, Raquel Urtasun:
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch. ICCV 2019: 4383-4392 - [c153]Yun Chen, Bin Yang, Ming Liang, Raquel Urtasun:
Learning Joint 2D-3D Representations for Depth Completion. ICCV 2019: 10022-10031 - [c152]Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel:
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. ICLR (Poster) 2019 - [c151]Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel:
LanczosNet: Multi-Scale Deep Graph Convolutional Networks. ICLR (Poster) 2019 - [c150]Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. ICLR (Poster) 2019 - [c149]Davi Frossard, Eric Kee, Raquel Urtasun:
DeepSignals: Predicting Intent of Drivers Through Visual Signals. ICRA 2019: 9697-9703 - [c148]Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. IROS 2019: 3949-3956 - [c147]Wei-Chiu Ma, Raquel Urtasun, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai
, Gellért Máttyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky:
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization. IROS 2019: 5304-5311 - [c146]Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel:
Efficient Graph Generation with Graph Recurrent Attention Networks. NeurIPS 2019: 4257-4267 - [i64]Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel:
LanczosNet: Multi-Scale Deep Graph Convolutional Networks. CoRR abs/1901.01484 (2019) - [i63]Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun:
UPSNet: A Unified Panoptic Segmentation Network. CoRR abs/1901.03784 (2019) - [i62]Bin Yang, Wenjie Luo, Raquel Urtasun:
PIXOR: Real-time 3D Object Detection from Point Clouds. CoRR abs/1902.06326 (2019) - [i61]Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, Raquel Urtasun:
Deep Rigid Instance Scene Flow. CoRR abs/1904.08913 (2019) - [i60]Davi Frossard, Eric Kee, Raquel Urtasun:
DeepSignals: Predicting Intent of Drivers Through Visual Signals. CoRR abs/1905.01333 (2019) - [i59]Min Bai, Gellért Máttyus, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Deep Multi-Sensor Lane Detection. CoRR abs/1905.01555 (2019) - [i58]Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun:
DARNet: Deep Active Ray Network for Building Segmentation. CoRR abs/1905.05889 (2019) - [i57]Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun:
Deformable Filter Convolution for Point Cloud Reasoning. CoRR abs/1907.13079 (2019) - [i56]Wei-Chiu Ma, Ignacio Tartavull, Ioan Andrei Bârsan, Shenlong Wang, Min Bai, Gellért Máttyus, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Andrei Pokrovsky, Raquel Urtasun:
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization. CoRR abs/1908.03274 (2019) - [i55]Jerry Liu
, Shenlong Wang, Raquel Urtasun:
DSIC: Deep Stereo Image Compression. CoRR abs/1908.03631 (2019) - [i54]Shivam Duggal, Shenlong Wang, Wei-Chiu Ma, Rui Hu, Raquel Urtasun:
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch. CoRR abs/1909.05845 (2019) - [i53]Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun:
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. CoRR abs/1909.12471 (2019) - [i52]Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel:
Efficient Graph Generation with Graph Recurrent Attention Networks. CoRR abs/1910.00760 (2019) - [i51]Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. CoRR abs/1910.04586 (2019) - [i50]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
Learning to Remember from a Multi-Task Teacher. CoRR abs/1910.04650 (2019) - [i49]Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun:
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. CoRR abs/1910.08041 (2019) - [i48]Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun:
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. CoRR abs/1910.08233 (2019) - [i47]Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRR abs/1910.11296 (2019) - [i46]Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Rui Hu, Raquel Urtasun:
PolyTransform: Deep Polygon Transformer for Instance Segmentation. CoRR abs/1912.02801 (2019) - [i45]Ze Yang, Yinghao Xu, Han Xue, Zheng Zhang, Raquel Urtasun, Liwei Wang, Stephen Lin, Han Hu:
Dense RepPoints: Representing Visual Objects with Dense Point Sets. CoRR abs/1912.11473 (2019) - 2018
- [j14]Xiaozhi Chen
, Kaustav Kundu, Yukun Zhu, Huimin Ma
, Sanja Fidler, Raquel Urtasun:
3D Object Proposals Using Stereo Imagery for Accurate Object Class Detection. IEEE Trans. Pattern Anal. Mach. Intell. 40(5): 1259-1272 (2018) - [j13]Patrick Judd
, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger
, Raquel Urtasun, Andreas Moshovos:
Proteus: Exploiting precision variability in deep neural networks. Parallel Comput. 73: 40-51 (2018) - [c145]Chris Zhang, Wenjie Luo, Raquel Urtasun:
Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds. 3DV 2018: 399-408 - [c144]Bin Yang, Ming Liang, Raquel Urtasun:
HDNET: Exploiting HD Maps for 3D Object Detection. CoRL 2018: 146-155 - [c143]Ioan Andrei Barsan
, Shenlong Wang, Andrei Pokrovsky, Raquel Urtasun:
Learning to Localize Using a LiDAR Intensity Map. CoRL 2018: 605-616 - [c142]Sergio Casas, Wenjie Luo, Raquel Urtasun:
IntentNet: Learning to Predict Intention from Raw Sensor Data. CoRL 2018: 947-956 - [c141]Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, Jiaya Jia:
GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation. CVPR 2018: 283-291 - [c140]Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun:
Deep Parametric Continuous Convolutional Neural Networks. CVPR 2018: 2589-2597 - [c139]Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
SurfConv: Bridging 3D and 2D Convolution for RGBD Images. CVPR 2018: 3002-3011 - [c138]Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Hierarchical Recurrent Attention Networks for Structured Online Maps. CVPR 2018: 3417-3426 - [c137]Wenjie Luo, Bin Yang, Raquel Urtasun:
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting With a Single Convolutional Net. CVPR 2018: 3569-3577 - [c136]Bin Yang, Wenjie Luo, Raquel Urtasun:
PIXOR: Real-Time 3D Object Detection From Point Clouds. CVPR 2018: 7652-7660 - [c135]Gellért Máttyus, Raquel Urtasun:
Matching Adversarial Networks. CVPR 2018: 8024-8032 - [c134]Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CVPR 2018: 8711-8720 - [c133]Diego Marcos
, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai
, Renjie Liao, Raquel Urtasun:
Learning Deep Structured Active Contours End-to-End. CVPR 2018: 8877-8885 - [c132]Wei-Chiu Ma, Hang Chu, Bolei Zhou, Raquel Urtasun, Antonio Torralba:
Single Image Intrinsic Decomposition Without a Single Intrinsic Image. ECCV (14) 2018: 211-229 - [c131]Justin Liang, Raquel Urtasun:
End-to-End Deep Structured Models for Drawing Crosswalks. ECCV (12) 2018: 407-423 - [c130]Ming Liang, Bin Yang, Shenlong Wang, Raquel Urtasun:
Deep Continuous Fusion for Multi-sensor 3D Object Detection. ECCV (16) 2018: 663-678 - [c129]Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel:
Graph Partition Neural Networks for Semi-Supervised Classification. ICLR (Workshop) 2018 - [c128]KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in probabilistic graphical models by Graph Neural Networks. ICLR (Workshop) 2018 - [c127]Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Raquel Urtasun, Richard S. Zemel:
Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. ICLR (Workshop) 2018 - [c126]Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel:
Reviving and Improving Recurrent Back-Propagation. ICML 2018: 3088-3097 - [c125]Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. ICML 2018: 4331-4340 - [c124]Davi Frossard, Raquel Urtasun:
End-to-end Learning of Multi-sensor 3D Tracking by Detection. ICRA 2018: 635-642 - [c123]Min Bai
, Gellért Máttyus, Namdar Homayounfar, Shenlong Wang, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun:
Deep Multi-Sensor Lane Detection. IROS 2018: 3102-3109 - [c122]Marvin Teichmann, Michael Weber, J. Marius Zöllner, Roberto Cipolla
, Raquel Urtasun:
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving. Intelligent Vehicles Symposium 2018: 1013-1020 - [c121]Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel:
Neural Guided Constraint Logic Programming for Program Synthesis. NeurIPS 2018: 1744-1753 - [i44]Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CoRR abs/1801.02108 (2018) - [i43]Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel:
Graph Partition Neural Networks for Semi-Supervised Classification. CoRR abs/1803.06272 (2018) - [i42]Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun:
Learning deep structured active contours end-to-end. CoRR abs/1803.06329 (2018) - [i41]Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel:
Reviving and Improving Recurrent Back-Propagation. CoRR abs/1803.06396 (2018) - [i40]KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow:
Inference in Probabilistic Graphical Models by Graph Neural Networks. CoRR abs/1803.07710 (2018) - [i39]Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. CoRR abs/1803.09050 (2018) - [i38]Davi Frossard, Raquel Urtasun:
End-to-end Learning of Multi-sensor 3D Tracking by Detection. CoRR abs/1806.11534 (2018) - [i37]Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard S. Zemel:
Neural Guided Constraint Logic Programming for Program Synthesis. CoRR abs/1809.02840 (2018) - [i36]Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. CoRR abs/1810.05749 (2018) - [i35]Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
SurfConv: Bridging 3D and 2D Convolution for RGBD Images. CoRR abs/1812.01519 (2018) - 2017
- [j12]Nina Merkle
, Wenjie Luo, Stefan Auer, Rupert Müller, Raquel Urtasun:
Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images. Remote. Sens. 9(6): 586 (2017) - [c120]Min Bai
, Raquel Urtasun:
Deep Watershed Transform for Instance Segmentation. CVPR 2017: 2858-2866 - [c119]Namdar Homayounfar, Sanja Fidler, Raquel Urtasun:
Sports Field Localization via Deep Structured Models. CVPR 2017: 4012-4020 - [c118]Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Annotating Object Instances with a Polygon-RNN. CVPR 2017: 4485-4493 - [c117]Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing:
Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. CVPR 2017: 5948-5956 - [c116]Shizhan Zhu, Sanja Fidler, Raquel Urtasun, Dahua Lin
, Chen Change Loy:
Be Your Own Prada: Fashion Synthesis with Structural Coherence. ICCV 2017: 1689-1697 - [c115]Bo Dai, Sanja Fidler, Raquel Urtasun, Dahua Lin
:
Towards Diverse and Natural Image Descriptions via a Conditional GAN. ICCV 2017: 2989-2998 - [c114]Shenlong Wang, Min Bai
, Gellért Máttyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun:
TorontoCity: Seeing the World with a Million Eyes. ICCV 2017: 3028-3036 - [c113]Gellért Máttyus, Wenjie Luo, Raquel Urtasun:
DeepRoadMapper: Extracting Road Topology from Aerial Images. ICCV 2017: 3458-3466 - [c112]Shu Liu, Jiaya Jia, Sanja Fidler, Raquel Urtasun:
SGN: Sequential Grouping Networks for Instance Segmentation. ICCV 2017: 3516-3524 - [c111]Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler:
Situation Recognition with Graph Neural Networks. ICCV 2017: 4183-4192 - [c110]Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun:
3D Graph Neural Networks for RGBD Semantic Segmentation. ICCV 2017: 5209-5218 - [c109]Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel:
Joint Embeddings of Scene Graphs and Images. ICLR (Workshop) 2017 - [c108]Hang Chu, Raquel Urtasun, Sanja Fidler:
Song From PI: A Musically Plausible Network for Pop Music Generation. ICLR (Workshop) 2017 - [c107]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. ICLR (Poster) 2017 - [c106]Marc T. Law, Raquel Urtasun, Richard S. Zemel:
Deep Spectral Clustering Learning. ICML 2017: 1985-1994 - [c105]Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker
, Sanja Fidler, Raquel Urtasun:
Find your way by observing the sun and other semantic cues. ICRA 2017: 6292-6299 - [c104]Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. NIPS 2017: 2214-2224 - [c103]Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun:
Few-Shot Learning Through an Information Retrieval Lens. NIPS 2017: 2255-2265 - [i34]Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel:
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks. CoRR abs/1701.04128 (2017) - [i33]Bo Dai, Dahua Lin, Raquel Urtasun, Sanja Fidler:
Towards Diverse and Natural Image Descriptions via a Conditional GAN. CoRR abs/1703.06029 (2017) - [i32]Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Annotating Object Instances with a Polygon-RNN. CoRR abs/1704.05548 (2017) - [i31]Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun:
Few-Shot Learning Through an Information Retrieval Lens. CoRR abs/1707.02610 (2017) - [i30]Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. CoRR abs/1707.04585 (2017) - [i29]Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler:
Situation Recognition with Graph Neural Networks. CoRR abs/1708.04320 (2017) - [i28]Shizhan Zhu, Sanja Fidler, Raquel Urtasun, Dahua Lin, Chen Change Loy:
Be Your Own Prada: Fashion Synthesis with Structural Coherence. CoRR abs/1710.07346 (2017) - 2016
- [j11]Tamir Hazan, Alexander G. Schwing, Raquel Urtasun:
Blending Learning and Inference in Conditional Random Fields. J. Mach. Learn. Res. 17: 237:1-237:25 (2016) - [j10]Roozbeh Mottaghi, Sanja Fidler, Alan L. Yuille
, Raquel Urtasun, Devi Parikh:
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 38(1): 74-87 (2016) - [j9]Marcus A. Brubaker
, Andreas Geiger, Raquel Urtasun:
Map-Based Probabilistic Visual Self-Localization. IEEE Trans. Pattern Anal. Mach. Intell. 38(4): 652-665 (2016) - [c102]Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun:
Sequential Inference for Deep Gaussian Process. AISTATS 2016: 694-703 - [c101]Raquel Urtasun:
Towards Affordable Self-driving Cars. BMVC 2016 - [c100]Ziyu Zhang, Sanja Fidler, Raquel Urtasun:
Instance-Level Segmentation for Autonomous Driving with Deep Densely Connected MRFs. CVPR 2016: 669-677 - [c99]Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, Raquel Urtasun:
Monocular 3D Object Detection for Autonomous Driving. CVPR 2016: 2147-2156 - [c98]Gellért Máttyus, Shenlong Wang, Sanja Fidler, Raquel Urtasun:
HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images. CVPR 2016: 3611-3619 - [c97]Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
MovieQA: Understanding Stories in Movies through Question-Answering. CVPR 2016: 4631-4640 - [c96]Wenjie Luo, Alexander G. Schwing, Raquel Urtasun:
Efficient Deep Learning for Stereo Matching. CVPR 2016: 5695-5703 - [c95]Min Bai
, Wenjie Luo, Kaustav Kundu, Raquel Urtasun:
Exploiting Semantic Information and Deep Matching for Optical Flow. ECCV (6) 2016: 154-170 - [c94]Hang Chu, Shenlong Wang, Raquel Urtasun, Sanja Fidler:
HouseCraft: Building Houses from Rental Ads and Street Views. ECCV (6) 2016: 500-516 - [c93]Yang Song, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Training Deep Neural Networks via Direct Loss Minimization. ICML 2016: 2169-2177 - [c92]Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Proximal Deep Structured Models. NIPS 2016: 865-873 - [c91]Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel:
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks. NIPS 2016: 4898-4906 - [c90]Renjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Learning Deep Parsimonious Representations. NIPS 2016: 5076-5084 - [c89]Eleni Triantafillou, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel:
Towards Generalizable Sentence Embeddings. Rep4NLP@ACL 2016: 239-248 - [c88]Ivan Vendrov, Ryan Kiros, Sanja Fidler, Raquel Urtasun:
Order-Embeddings of Images and Language. ICLR 2016 - [i27]Min Bai, Wenjie Luo, Kaustav Kundu, Raquel Urtasun:
Deep Semantic Matching for Optical Flow. CoRR abs/1604.01827 (2016) - [i26]Namdar Homayounfar, Sanja Fidler, Raquel Urtasun:
Soccer Field Localization from a Single Image. CoRR abs/1604.02715 (2016) - [i25]Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun:
Find your Way by Observing the Sun and Other Semantic Cues. CoRR abs/1606.07415 (2016) - [i24]Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Huimin Ma, Sanja Fidler, Raquel Urtasun:
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection. CoRR abs/1608.07711 (2016) - [i23]Wenyuan Zeng, Wenjie Luo, Sanja Fidler, Raquel Urtasun:
Efficient Summarization with Read-Again and Copy Mechanism. CoRR abs/1611.03382 (2016) - [i22]Hang Chu, Raquel Urtasun, Sanja Fidler:
Song From PI: A Musically Plausible Network for Pop Music Generation. CoRR abs/1611.03477 (2016) - [i21]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. CoRR abs/1611.04520 (2016) - [i20]Min Bai, Raquel Urtasun:
Deep Watershed Transform for Instance Segmentation. CoRR abs/1611.08303 (2016) - [i19]Shenlong Wang, Min Bai, Gellért Máttyus, Hang Chu, Wenjie Luo, Bin Yang, Justin Liang, Joel Cheverie, Sanja Fidler, Raquel Urtasun:
TorontoCity: Seeing the World with a Million Eyes. CoRR abs/1612.00423 (2016) - [i18]Marvin Teichmann, Michael Weber, J. Marius Zöllner, Roberto Cipolla, Raquel Urtasun:
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving. CoRR abs/1612.07695 (2016) - 2015
- [c87]Dahua Lin
, Sanja Fidler, Chen Kong, Raquel Urtasun:
Generating Multi-sentence Natural Language Descriptions of Indoor Scenes. BMVC 2015: 93.1-93.13 - [c86]Edgar Simo-Serra, Sanja Fidler, Francesc Moreno-Noguer, Raquel Urtasun:
Neuroaesthetics in fashion: Modeling the perception of fashionability. CVPR 2015: 869-877 - [c85]Jian Yao, Marko Boben, Sanja Fidler, Raquel Urtasun:
Real-time coarse-to-fine topologically preserving segmentation. CVPR 2015: 2947-2955 - [c84]Chenxi Liu, Alexander G. Schwing, Kaustav Kundu, Raquel Urtasun, Sanja Fidler:
Rent3D: Floor-plan priors for monocular layout estimation. CVPR 2015: 3413-3421 - [c83]Jia Xu, Alexander G. Schwing, Raquel Urtasun:
Learning to segment under various forms of weak supervision. CVPR 2015: 3781-3790 - [c82]Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Holistic 3D scene understanding from a single geo-tagged image. CVPR 2015: 3964-3972 - [c81]Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting segmentation and context in deep neural networks for object detection. CVPR 2015: 4703-4711 - [c80]Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books. ICCV 2015: 19-27 - [c79]Gellért Máttyus, Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Enhancing Road Maps by Parsing Aerial Images Around the World. ICCV 2015: 1689-1697 - [c78]Ziyu Zhang, Alexander G. Schwing, Sanja Fidler, Raquel Urtasun:
Monocular Object Instance Segmentation and Depth Ordering with CNNs. ICCV 2015: 2614-2622 - [c77]Shenlong Wang, Sanja Fidler, Raquel Urtasun:
Lost Shopping! Monocular Localization in Large Indoor Spaces. ICCV 2015: 2695-2703 - [c76]Philip Lenz, Andreas Geiger, Raquel Urtasun:
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation. ICCV 2015: 4364-4372 - [c75]Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun:
Learning Deep Structured Models. ICML 2015: 1785-1794 - [c74]Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G. Berneshawi, Huimin Ma, Sanja Fidler, Raquel Urtasun:
3D Object Proposals for Accurate Object Class Detection. NIPS 2015: 424-432 - [c73]Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Skip-Thought Vectors. NIPS 2015: 3294-3302 - [c72]Jian Yao, Srikumar Ramalingam, Yuichi Taguchi, Yohei Miki, Raquel Urtasun:
Estimating Drivable Collision-Free Space from Monocular Video. WACV 2015: 420-427 - [c71]Liang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun:
Learning Deep Structured Models. ICLR (Workshop) 2015 - [i17]Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection. CoRR abs/1502.04275 (2015) - [i16]Dahua Lin, Chen Kong, Sanja Fidler, Raquel Urtasun:
Generating Multi-Sentence Lingual Descriptions of Indoor Scenes. CoRR abs/1503.00064 (2015) - [i15]Alexander G. Schwing, Raquel Urtasun:
Fully Connected Deep Structured Networks. CoRR abs/1503.02351 (2015) - [i14]Ziyu Zhang, Alexander G. Schwing, Sanja Fidler, Raquel Urtasun:
Monocular Object Instance Segmentation and Depth Ordering with CNNs. CoRR abs/1505.03159 (2015) - [i13]Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books. CoRR abs/1506.06724 (2015) - [i12]Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
Skip-Thought Vectors. CoRR abs/1506.06726 (2015) - [i11]Patrick Judd, Jorge Albericio, Tayler H. Hetherington, Tor M. Aamodt, Natalie D. Enright Jerger, Raquel Urtasun, Andreas Moshovos:
Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets. CoRR abs/1511.05236 (2015) - [i10]Yang Song, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun:
Direct Loss Minimization for Training Deep Neural Nets. CoRR abs/1511.06411 (2015) - [i9]Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
MovieQA: Understanding Stories in Movies through Question-Answering. CoRR abs/1512.02902 (2015) - [i8]Ziyu Zhang, Sanja Fidler, Raquel Urtasun:
Instance-Level Segmentation with Deep Densely Connected MRFs. CoRR abs/1512.06735 (2015) - 2014
- [j8]Andreas Geiger, Martin Lauer
, Christian Wojek, Christoph Stiller
, Raquel Urtasun:
3D Traffic Scene Understanding From Movable Platforms. IEEE Trans. Pattern Anal. Mach. Intell. 36(5): 1012-1025 (2014) - [c70]Edgar Simo-Serra, Sanja Fidler, Francesc Moreno-Noguer, Raquel Urtasun:
A High Performance CRF Model for Clothes Parsing. ACCV (3) 2014: 64-81 - [c69]Roozbeh Mottaghi, Xianjie Chen, Xiaobai Liu, Nam-Gyu Cho
, Seong-Whan Lee, Sanja Fidler, Raquel Urtasun, Alan L. Yuille
:
The Role of Context for Object Detection and Semantic Segmentation in the Wild. CVPR 2014: 891-898 - [c68]Xianjie Chen, Roozbeh Mottaghi, Xiaobai Liu, Sanja Fidler, Raquel Urtasun, Alan L. Yuille
:
Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts. CVPR 2014: 1979-1986 - [c67]Dahua Lin
, Sanja Fidler, Chen Kong, Raquel Urtasun:
Visual Semantic Search: Retrieving Videos via Complex Textual Queries. CVPR 2014: 2657-2664 - [c66]Jia Xu, Alexander G. Schwing, Raquel Urtasun:
Tell Me What You See and I Will Show You Where It Is. CVPR 2014: 3190-3197 - [c65]Liang-Chieh Chen, Sanja Fidler, Raquel Urtasun:
Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision. CVPR 2014: 3198-3205 - [c64]Chen Kong, Dahua Lin
, Mohit Bansal, Raquel Urtasun, Sanja Fidler:
What Are You Talking About? Text-to-Image Coreference. CVPR 2014: 3558-3565 - [c63]Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun:
Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation. ECCV (5) 2014: 756-771 - [c62]Shenlong Wang, Lei Zhang
, Raquel Urtasun:
Transductive Gaussian processes for image denoising. ICCP 2014: 1-8 - [c61]Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm. ICML 2014: 487-495 - [c60]Shenlong Wang, Alexander G. Schwing, Raquel Urtasun:
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials. NIPS 2014: 936-944 - [c59]Jian Zhang, Alexander G. Schwing, Raquel Urtasun:
Message Passing Inference for Large Scale Graphical Models with High Order Potentials. NIPS 2014: 1134-1142 - [c58]Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun:
Bayesian Filtering with Online Gaussian Process Latent Variable Models. UAI 2014: 849-857 - [i7]Xianjie Chen, Roozbeh Mottaghi, Xiaobai Liu, Sanja Fidler, Raquel Urtasun, Alan L. Yuille:
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts. CoRR abs/1406.2031 (2014) - [i6]Roozbeh Mottaghi, Sanja Fidler, Alan L. Yuille, Raquel Urtasun, Devi Parikh:
Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding. CoRR abs/1406.3906 (2014) - [i5]Philip Lenz, Andreas Geiger, Raquel Urtasun:
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation. CoRR abs/1407.6251 (2014) - 2013
- [j7]Andreas Geiger, Philip Lenz, Christoph Stiller
, Raquel Urtasun:
Vision meets robotics: The KITTI dataset. Int. J. Robotics Res. 32(11): 1231-1237 (2013) - [c57]Koichiro Yamaguchi, David A. McAllester, Raquel Urtasun:
Robust Monocular Epipolar Flow Estimation. CVPR 2013: 1862-1869 - [c56]Sanja Fidler, Abhishek Sharma, Raquel Urtasun:
A Sentence Is Worth a Thousand Pixels. CVPR 2013: 1995-2002 - [c55]Marcus A. Brubaker
, Andreas Geiger, Raquel Urtasun:
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization. CVPR 2013: 3057-3064 - [c54]Roozbeh Mottaghi, Sanja Fidler, Jian Yao, Raquel Urtasun, Devi Parikh:
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs. CVPR 2013: 3143-3150 - [c53]Sanja Fidler, Roozbeh Mottaghi, Alan L. Yuille
, Raquel Urtasun:
Bottom-Up Segmentation for Top-Down Detection. CVPR 2013: 3294-3301 - [c52]Alexander G. Schwing, Sanja Fidler, Marc Pollefeys
, Raquel Urtasun:
Box in the Box: Joint 3D Layout and Object Reasoning from Single Images. ICCV 2013: 353-360 - [c51]Jian Zhang, Chen Kan, Alexander G. Schwing, Raquel Urtasun:
Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors. ICCV 2013: 1273-1280 - [c50]Dahua Lin
, Sanja Fidler, Raquel Urtasun:
Holistic Scene Understanding for 3D Object Detection with RGBD Cameras. ICCV 2013: 1417-1424 - [c49]Hongyi Zhang, Andreas Geiger, Raquel Urtasun:
Understanding High-Level Semantics by Modeling Traffic Patterns. ICCV 2013: 3056-3063 - [c48]Wenjie Luo, Alexander G. Schwing, Raquel Urtasun:
Latent Structured Active Learning. NIPS 2013: 728-736 - 2012
- [c47]Jian Yao, Sanja Fidler, Raquel Urtasun:
Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation. CVPR 2012: 702-709 - [c46]Aydin Varol, Mathieu Salzmann, Pascal Fua
, Raquel Urtasun:
A constrained latent variable model. CVPR 2012: 2248-2255 - [c45]Alexander G. Schwing, Tamir Hazan, Marc Pollefeys
, Raquel Urtasun:
Efficient structured prediction for 3D indoor scene understanding. CVPR 2012: 2815-2822 - [c44]Andreas Geiger, Philip Lenz, Raquel Urtasun:
Are we ready for autonomous driving? The KITTI vision benchmark suite. CVPR 2012: 3354-3361 - [c43]Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Continuous Markov Random Fields for Robust Stereo Estimation. ECCV (5) 2012: 45-58 - [c42]Mathieu Salzmann, Raquel Urtasun:
Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction. ECCV (4) 2012: 245-259 - [c41]Alexander G. Schwing, Raquel Urtasun:
Efficient Exact Inference for 3D Indoor Scene Understanding. ECCV (6) 2012: 299-313 - [c40]Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Efficient Structured Prediction with Latent Variables for General Graphical Models. ICML 2012 - [c39]Sanja Fidler, Sven J. Dickinson, Raquel Urtasun:
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model. NIPS 2012: 620-628 - [c38]Alexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun:
Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins. NIPS 2012: 2393-2401 - [c37]Marcus A. Brubaker, Mathieu Salzmann, Raquel Urtasun:
A Family of MCMC Methods on Implicitly Defined Manifolds. AISTATS 2012: 161-172 - [i4]Koichiro Yamaguchi, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Continuous Markov Random Fields for Robust Stereo Estimation. CoRR abs/1204.1393 (2012) - [i3]C. Mario Christoudias, Raquel Urtasun, Trevor Darrell:
Multi-View Learning in the Presence of View Disagreement. CoRR abs/1206.3242 (2012) - [i2]Tamir Hazan, Raquel Urtasun:
Efficient Learning of Structured Predictors in General Graphical Models. CoRR abs/1210.2346 (2012) - 2011
- [c36]Alexander G. Schwing, Tamir Hazan, Marc Pollefeys
, Raquel Urtasun:
Distributed message passing for large scale graphical models. CVPR 2011: 1833-1840 - [c35]Andreas Geiger, Martin Lauer
, Raquel Urtasun:
A generative model for 3D urban scene understanding from movable platforms. CVPR 2011: 1945-1952 - [c34]Alex Shyr, Trevor Darrell, Michael I. Jordan
, Raquel Urtasun:
Supervised hierarchical Pitman-Yor process for natural scene segmentation. CVPR 2011: 2281-2288 - [c33]Henning Hamer, Juergen Gall, Raquel Urtasun, Luc Van Gool:
Data-driven animation of hand-object interactions. FG 2011: 360-367 - [c32]Mathieu Salzmann, Raquel Urtasun:
Physically-based motion models for 3D tracking: A convex formulation. ICCV 2011: 2064-2071 - [c31]Jian Peng, Tamir Hazan, David A. McAllester, Raquel Urtasun:
Convex Max-Product over Compact Sets for Protein Folding. ICML 2011: 729-736 - [c30]Angela Yao, Juergen Gall, Luc Van Gool, Raquel Urtasun:
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities. NIPS 2011: 1359-1367 - [c29]Andreas Geiger, Christian Wojek, Raquel Urtasun:
Joint 3D Estimation of Objects and Scene Layout. NIPS 2011: 1467-1475 - 2010
- [j6]Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Trevor Darrell:
Gaussian Processes for Object Categorization. Int. J. Comput. Vis. 88(2): 169-188 (2010) - [c28]Andreas Geiger, Martin Roser, Raquel Urtasun:
Efficient Large-Scale Stereo Matching. ACCV (1) 2010: 25-38 - [c27]Mathieu Salzmann, Raquel Urtasun:
Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction. CVPR 2010: 647-654 - [c26]Alex Shyr, Raquel Urtasun, Michael I. Jordan
:
Sufficient dimension reduction for visual sequence classification. CVPR 2010: 3610-3617 - [c25]C. Mario Christoudias, Raquel Urtasun, Mathieu Salzmann, Trevor Darrell:
Learning to Recognize Objects from Unseen Modalities. ECCV (1) 2010: 677-691 - [c24]Tamir Hazan, Raquel Urtasun:
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction. NIPS 2010: 838-846 - [c23]Taehwan Kim, Gregory Shakhnarovich, Raquel Urtasun:
Sparse Coding for Learning Interpretable Spatio-Temporal Primitives. NIPS 2010: 1117-1125 - [c22]Mathieu Salzmann, Raquel Urtasun:
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation. NIPS 2010: 2065-2073 - [c21]Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, Trevor Darrell:
Factorized Orthogonal Latent Spaces. AISTATS 2010: 701-708 - [i1]Tamir Hazan, Raquel Urtasun:
Approximated Structured Prediction for Learning Large Scale Graphical Models. CoRR abs/1006.2899 (2010)
2000 – 2009
- 2009
- [c20]Andreas Geiger, Raquel Urtasun, Trevor Darrell:
Rank priors for continuous non-linear dimensionality reduction. CVPR 2009: 880-887 - [c19]C. Mario Christoudias, Raquel Urtasun, Ashish Kapoor, Trevor Darrell:
Co-training with noisy perceptual observations. CVPR 2009: 2844-2851 - [c18]Neil D. Lawrence
, Raquel Urtasun:
Non-linear matrix factorization with Gaussian processes. ICML 2009: 601-608 - 2008
- [c17]C. Mario Christoudias, Raquel Urtasun, Trevor Darrell:
Unsupervised feature selection via distributed coding for multi-view object recognition. CVPR 2008 - [c16]Mathieu Salzmann, Raquel Urtasun, Pascal Fua
:
Local deformation models for monocular 3D shape recovery. CVPR 2008 - [c15]Raquel Urtasun, Trevor Darrell:
Sparse probabilistic regression for activity-independent human pose inference. CVPR 2008 - [c14]Raquel Urtasun, David J. Fleet, Andreas Geiger, Jovan Popovic, Trevor Darrell, Neil D. Lawrence
:
Topologically-constrained latent variable models. ICML 2008: 1080-1087 - 2007
- [c13]David Demirdjian, Raquel Urtasun:
Patch-Based Pose Inference with a Mixture of Density Estimators. AMFG 2007: 96-108 - [c12]Raquel Urtasun, David J. Fleet, Neil D. Lawrence:
Modeling Human Locomotion with Topologically Constrained Latent Variable Models. Workshop on Human Motion 2007: 104-118 - [c11]Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Trevor Darrell:
Active Learning with Gaussian Processes for Object Categorization. ICCV 2007: 1-8 - [c10]Raquel Urtasun, Trevor Darrell:
Discriminative Gaussian process latent variable model for classification. ICML 2007: 927-934 - 2006
- [j5]Raquel Urtasun, David J. Fleet
, Pascal Fua
:
Temporal motion models for monocular and multiview 3D human body tracking. Comput. Vis. Image Underst. 104(2-3): 157-177 (2006) - [c9]Raquel Urtasun, David J. Fleet
, Pascal Fua
:
3D People Tracking with Gaussian Process Dynamical Models. CVPR (1) 2006: 238-245 - 2005
- [j4]Lorna Herda, Raquel Urtasun, Pascal Fua
:
Hierarchical implicit surface joint limits for human body tracking. Comput. Vis. Image Underst. 99(2): 189-209 (2005) - [c8]Raquel Urtasun, David J. Fleet
, Pascal Fua
:
Monocular 3-D Tracking of the Golf Swing. CVPR (2) 2005: 932-938 - [c7]Raquel Urtasun, David J. Fleet, Pascal Fua:
Monocular 3D Tracking of the Golf Swing. CVPR (2) 2005: 1199 - [c6]Raquel Urtasun, David J. Fleet
, Aaron Hertzmann
, Pascal Fua
:
Priors for People Tracking from Small Training Sets. ICCV 2005: 403-410 - 2004
- [j3]Raquel Urtasun, Pascal Glardon, Ronan Boulic, Daniel Thalmann, Pascal Fua
:
Style-Based Motion Synthesis. Comput. Graph. Forum 23(4): 799-812 (2004) - [c5]Raquel Urtasun, Pascal Fua:
3D Human Body Tracking Using Deterministic Temporal Motion Models. ECCV (3) 2004: 92-106 - [c4]Lorna Herda, Raquel Urtasun, Pascal Fua:
Hierarchical Implicit Surface Joint Limits to Constrain Video-Based Motion Capture. ECCV (2) 2004: 405-418 - [c3]Raquel Urtasun, Pascal Fua
:
3D Tracking for Gait Characterization and Recognition. FGR 2004: 17-22 - 2003
- [j2]Lorna Herda, Raquel Urtasun, Pascal Fua, Andrew J. Hanson:
Automatic Determination of Shoulder Joint Limits Using Quaternion Field Boundaries. Int. J. Robotics Res. 22(6): 419-438 (2003) - [j1]Petr Dokládal, Isabelle Bloch, Michel Couprie, Daniel Ruijters
, Raquel Urtasun, Line Garnero:
opologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators. Pattern Recognit. 36(10): 2463-2478 (2003) - 2002
- [c2]Lorna Herda, Raquel Urtasun, Pascal Fua
, Andrew J. Hanson:
An Automatic Method For Determining Quaternion Field Boundaries for Ball-and-Socket Joint Limits. FGR 2002: 95-100 - 2001
- [c1]Petr Dokládal, Raquel Urtasun, Isabelle Bloch, Line Garnero:
Segmentation of 3D head MR images using morphological reconstruction under constraints and automatic selection of markers. ICIP (3) 2001: 1075-1078
Coauthor Index
aka: Ioan Andrei Bârsan
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