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2021
- J. Tu, H. Li, X. Yan, M. Ren, Y. Chen, M. Liang, E. Bitar, E. Yumer and R. Urtasun
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving [pdf] 
In Conference on Robot Learning (CoRL), London UK, November 2021
- S. Segal, N. Kumar, S. Casas, W. Zeng, M. Ren, J. Wang, and R. Urtasun
Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes [pdf] 
In Conference on Robot Learning (CoRL), London UK, November 2021
- A. Cui, A. Sadat, S. Casas, R. Liao, R. Urtasun
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving [pdf]  (oral)
In International Conference on Computer Vision (ICCV), October 2021
- J. Tu, T. Wang, J. Wang, S. Manivasagam, M. Ren and R. Urtasun
Adversarial Attacks On Multi-Agent Communication [pdf] 
In International Conference on Computer Vision (ICCV), October 2021
- Y. Xiong, M. Ren, W. Zeng, R. Urtasun
Self-Supervised Representation Learning from Flow Equivariance [pdf] 
In International Conference on Computer Vision (ICCV), October 2021
- K. Luo, S. Casas, R. Liao, X. Yan, Y. Xiong, W. Zeng and R. Urtasun
Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting [pdf] 
In International Conference on Intelligent Robots and Systems (IROS), Prague, Check Republic, October 2021
- Y. Wang, B. Yang, R. Hu, M. Liang, and R. Urtasun
PLUME: Efficient 3D Object Detection from Stereo Images [pdf] 
In International Conference on Intelligent Robots and Systems (IROS), Prague, Check Republic, October 2021
- A. Sadat, S. Segal, S. Casas, J. Tu, B. Yang, R. Urtasun and E. Yumer
Diverse Complexity Measures for Dataset Curation in Self-driving [pdf] 
In International Conference on Intelligent Robots and Systems (IROS), Prague, Check Republic, October 2021
- Y. Chen, F. Rong, S. Duggal, S. Wang, X. Yan, S. Manivasagam, S. Xue, E. Yumer R. Urtasun
GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition [pdf]  (Finalist Best Paper Award)
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- S. Casas, A. Sadat and R. Urtasun
MP3: A Unified Model to Map, Perceive, Predict and Plan [pdf]  (Finalist Best Paper Award)
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- J. Martinez, J. Shewakramani, T. Wei Liu, A. Barsan, W. Zeng, and R. Urtasun
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- J. Wang, A. Pun, J. Tu, S. Manivasagam, A. Sadat, S. Casas, M. Ren, R. Urtasun
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- Z. Yang, S. Wang, S. Manivasagam, Z. Huang, W-C. Ma, X. Yan, E. Yumer and R. Urtasun
S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- S. Suo, S. Regalado, S. Casas and R. Urtasun
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- S. Tan, K. Wong, S. Wang, S. Manivasagam, M. Ren and R. Urtasun
SceneGen: Learning to Generate Realistic Traffic Scenes [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- J. Phillips, J. Martinez, I. A. Bârsan, S. Casas, A. Sadat and R. Urtasun
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Virtual, June 2021
- B. Wei*, M. Ren*, W. Zeng, M. Liang, B. Yang and R. Urtasun
Perceive, attend, and drive: Learning spatial attention for safe self-driving [pdf] 
In International Conference on Robotics and Automation (ICRA), Xian, China, May 2021
- A. J. Yang, C. Cui, I. A. Barsan, R. Urtasun and S. Wang
Asynchronous Multi-View SLAM [pdf] 
In International Conference on Robotics and Automation (ICRA), Xian, China, May 2021
- J. Liu, W. Zeng, R. Urtasun and E. Yumer
Deep Structured Reactive Planning [pdf] 
In International Conference on Robotics and Automation (ICRA), Xian, China, May 2021
- R. Liao, R. Urtasun and R. Zemel
PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks [pdf] 
In International Conference on Learning Representations (ICLR), Vienna, Austria, May 2021
- X. Zeng, R. Urtasun, R. Zemel, S. Fidler and R. Liao
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation[pdf] 
In Arxiv preprint, arXiv:2106.13435, June 2021
- B. Yang, M. Bai, M. Liang, W. Zeng and R. Urtasun
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds [pdf] 
In Arxiv preprint, arXiv:2101.06586, Jan 2021
- N. Homayounfar, J. Liang, W.-C. Ma R. Urtasun
VideoClick: Video Object Segmentation with a Single Click [pdf] 
In Arxiv preprint, arXiv:2101.06545, Jan 2021
- M. Bai, S. Wang, K. Wong, E. Yumer and R. Urtasun
Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving [pdf] 
In Arxiv preprint, arXiv:2101.06865, Jan 2021
- S. Duggal, Z. Wang, W-C Ma, S. Manivasagam, J. Liang, S. Wang and R. Urtasun
Secrets of 3D Implicit Object Shape Reconstruction in the Wild [pdf] 
In Arxiv preprint, arXiv:2101.06860, Jan 2021
- W. Zeng, Y. Xiong and R. Urtasun
Network Automatic Pruning: Start NAP and Take a Nap [pdf] 
In Arxiv preprint, arXiv:2101.06608, Jan 2021
- J. Wang, M. Ren, I. Bogunovic, Y. Xiong and R. Urtasun
Cost-Efficient Online Hyperparameter Optimization [pdf] 
In Arxiv preprint, arXiv:2101.06590, Jan 2021
2020
- D. Frossard, S. Suo, S. Casas, J. Tu and R. Urtasun
StrObe: Streaming Object Detection from LiDAR Packets [pdf] 
In Conference on Robot Learning (CoRL), Cambridge, Massachusetts, US, November 2020
- S. Segal, E. Kee, W. Luo, A. Sadat, E. Yumer and R. Urtasun
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs [pdf]  (oral)
In Conference on Robot Learning (CoRL), Cambridge, Massachusetts, US, November 2020
- Z. Yang, S. Manivasagam, M. Liang, B. Yang, W-C. Ma and R. Urtasun
Recovering and Simulating Pedestrians in the Wild [pdf] 
In Conference on Robot Learning (CoRL), Cambridge, Massachusetts, US, November 2020
- M. Shah, Z. Huang, A. Laddha, M. Langford, B. Barber, S. Zhang, C. Vallespi-Gonzalez and R. Urtasun
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion [pdf] 
In Conference on Robot Learning (CoRL), Cambridge, Massachusetts, US, November 2020
- N. Vadivelu, M. Ren, J. Tu, J. Wang and R. Urtasun
Learning to Communicate and Correct Pose Errors [pdf] 
In Conference on Robot Learning (CoRL), Cambridge, Massachusetts, US, November 2020
- Y. Xiong, M. Ren and R. Urtasun
LoCo: Local Contrastive Representation Learning [pdf] 
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020
- S. Biswas, J. Liu, K. Wong, S. Wang and R. Urtasun
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models [pdf] 
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2020
- J. Martinez, S. Doubov, J. Fan, I. A. Barsan, S. Wang, G. Mattyus and R. Urtasun
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars [pdf coming soon]  (Finalist Best Applicaton Paper Award)
In International Conference on Intelligent Robots and Systems (IROS), Las Vegas, Nevada, US, November 2019
- S. Casas, C. Gulino, S. Su and R. Urtasun
The Importance of Prior Knowledge in Precise Multimodal Prediction [pdf]  (oral)
In International Conference on Intelligent Robots and Systems (IROS), Las Vegas, Nevada, US, November 2019
- L. Li, B. Yang, M. Liang, W. Zeng, M. Ren, S. Segal and R. Urtasun
End-to-end Contextual Perception and Prediction with Interaction Transformer [pdf]  (oral)
In International Conference on Intelligent Robots and Systems (IROS), Las Vegas, Nevada, US, November 2019
- X. Qi, Z. Liu, R. Liao, P. H. S. Torr, R. Urtasun and J. Jia
GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation [pdf] 
In Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020
- T-H. Wang, S. Manivasagam, M. Liang, B. Yang, W. Zeng and R. Urtasun
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction [pdf]  (oral)
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- M. Liang, B. Yang, R. Hu, Y. Chen, R. Liao, S. Feng and R. Urtasun
Learning Lane Graph Representations for Motion Forecasting [pdf]  (oral)
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- W-C. Ma, S. Wang, J. Gu, S. Manivasagam, A. Torralba and R. Urtasun
Deep Feedback Inverse Problem Solver [pdf]  (spotlight)
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- J. Gu, W-C. Ma, S. Manivasagam, W. Zeng, Z. Wang, Y. Xiong, Hao Su and R. Urtasun
Weakly-supervised 3D Shape Completion in the Wild [pdf]  (spotlight)
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- A. Sadat*, S. Casas*, M. Ren, X. Wu, P, Dhawan and R. Urtasun
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- W. Zeng, S. Wang, R. Liao, Y. Chen, B. Yang R. Urtasun
DSDNet: Deep Structured self-Driving Network [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- S. Casas*, C. Gulino*, S. Suo*, K. Luo, R. Liao and R. Urtasun
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- K. Wong, Q. Zhang, M. Liang, B. Yang, R. Liao, A. Sadat and R. Urtasun
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- N. Homayounfar, Y. Xiong, J. Liang, W-C. Ma and R. Urtasun
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- B. Yang*, R. Guo*, M. Liang, S. Casasn and R. Urtasun
RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- J. Liu, S. Wang, W-C. Ma, M. Shah, R. Hu, P. Dhawan and R. Urtasun
Conditional Entropy Coding for Efficient Video Compression [pdf coming soon] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- Z. Yang, Y. Xu, H. Xue, Z. Zhang, R. Urtasun, Liwei Wang, Stephen Lin and Han Hu
Dense RepPoints: Representing Visual Objects with Dense Point Sets [pdf] 
In European Conference in Computer Vision (ECCV), Glasgow, Scottland, August 2020
- Q. Sykora, M. Ren and R. Urtasun
Multi-Agent Routing Value Iteration Network [pdf]  (oral)
In International Conference in Machine Learning (ICML), Viena, Austria, July 2020
- C. H. Lim R. Urtasun and E. Yumer
Hierarchical Verification for Adversarial Robustness [pdf]  (oral)
In International Conference in Machine Learning (ICML), Viena, Austria, July 2020
- S. Manivasagam, S. Wang, K. Wong, W. Zeng, B. Yang, S. Tan, M. Sazanovich, W.C. Ma and R. Urtasun
LidarSIM: Realistic LiDAR Simulation by Leveraging the Real World [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020
- L. Huang, S. Wang, K. Wong, J. Liu and R. Urtasun
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020
- J. Tu, M. Ren, S. Manivasagam, M. Liang, B. Yang, R. Du, F. Cheng and R. Urtasun
Physically Realizable Adversarial Examples for LiDAR Object Detection [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020
- M. Liang*, B. Yang*, W. Zeng, Y. Chen, R. Hu, S. Casas and R. Urtasun
PnPNet: End-to-End Perception and Prediction with Tracking in the Loop [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020
- J. Liang, N. Homayounfar, W.C. Ma, Y. Xiong, R. Hu and R. Urtasun
PolyTransform: Deep Polygon Transformer for Instance Segmentation [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2020
- S. Casas, C. Gulino, R. Liao and R. Urtasun
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data [pdf]  (oral)
In International Conference on Robotics and Automation (ICRA), Paris, France, May 2020
2019
- R. Liao, Y. Li, Y. Song, S. Wang, W. Hamilton, D. Duvenaud, R. Urtasun and R. Zemel
Efficient Graph Generation with Graph Recurrent Attention Networks [pdf] 
In Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019
- K. Wong, S. Wang, M. Ren, M. Liang and R. Urtasun
Identifying Unknown Instances for Autonomous Driving [pdf]  (spotlight)
In Conference on Robot Learning (CoRL), Osaka, Japan, November 2019
- A. Jain, S. Casas, R. Liao, Y. Xiong, S. Feng, S. Segal and R. Urtasun
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction [pdf]  (spotlight)
In Conference on Robot Learning (CoRL), Osaka, Japan, November 2019
- Y. Xiong*, M. Ren*, R. Liao, K. Wong and R. Urtasun
Deformable Filter Convolution for Point Cloud Reasoning [pdf] 
In Arxiv preprint, arXiv:1907.13079, July 2019
- A. Sadat*, M. Ren*, A. Pokrovsky, Y. C. Lin, E. Yumer and R. Urtasun
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles [pdf]  (oral)
In International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019
- W.C Ma*, I. Tartavull*, I. A. Barsan*, S. Wang*, M. Bai, G. Mattyus, N. Homayounfar, S. K. Lakshmikanth, A. Pokrovsky and R. Urtasun
Exploiting Sparse Semantic HD Maps for Affordable Localization [pdf]  (oral)
In International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019
- J. Liu, S. Wang and R. Urtasun
Deep Stereo Image Compression [pdf]  (oral)
In International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019
- N. Homayounfar*, J. Liang*, W. C. Ma, J. Fan, X. Wu and R. Urtasun
DAGMapper: Learning to Map by Discovering Lane Topology [pdf] 
In International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019
- S. Duggal, S. Wang, W. C. Ma, R. Hu and R. Urtasun
Differentiable Deep PatchMatch for Efficient Stereo Matching [pdf] 
In International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019
- Y. Chen, M. Liang, B. Yang and R. Urtasun
Learning Joint 2D-3D Representations for Depth Completion [pdf] 
In International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019
- X. Zeng, R. Liao, L. Gu, Y. Xiong, S. Fidler R. Urtasun
DMM-Net: Differentiable Mask-Matching Network for Video Instance Segmentation [pdf] 
In International Conference on Computer Vision (ICCV), Seoul, Korea, October 2019
- W. Zeng*, W. Luo*, S. Suo, A. Saddat, B. Yang, S. Casas and R. Urtasun
End-to-end Interpretable Neural Motion Planner [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- Y. Xiong*, R. Liao*, H. Zhang*, R. Hui, E. Yumer and R. Urtasun
UPSNet: A Unified Panoptic Segmentation Network [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- W.C. Ma, S. Wang, R. Hu, Y. Xiong and R. Urtasun
Deep Structured Scene Flow [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- D. Chen, R. Liao, S. Fidler and R. Urtasun
DARNet: Deep Active Ray Network for Building Segmentation [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- M Liang*, B. Yang*, Y. Chen, R. Hui and R. Urtasun
Multi-Task Multi-Sensor Fusion for 3D Object Detection [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- X. Wei*, S. Wang*, J. Martinez, A. Barsan and R. Urtasun
Learning to Localize through Compressed Binary Maps [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- J. Liang*, N. Homayounfar*, S. Wang, W. C. Ma and R. Urtasun
Convolutional Recurrent Network for Road Boundary Extraction [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, June 2019
- D. Frossard, E. Kee and R. Urtasun
DeepSignals: Predicting Intent of Drivers Through Visual Attributes [pdf] 
In International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019
- R. Liao, Z. Zhao, R. Urtasun and R. Zemel
LanczosNet: Multi-Scale Deep Graph Convolutional Networks [pdf] 
In International Conference on Learning Representations, (ICLR), New Orleans, May 2019
- C. Zhang, M. Ren and R. Urtasun
Graph HyperNetworks for Neural Architecture Search [pdf] 
In International Conference on Learning Representations, (ICLR), New Orleans, May 2019
- M. T Law, J. Snell, A.Farahmand, R. Urtasun and R. Zemel
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models [pdf] 
In International Conference on Learning Representations, (ICLR), LNew Orleans, May 2019
2018
- L. Zhang, G. Rosenblatt, E. Fetaya, R. Liao, W. E Byrd, R. Urtasun and R. Zemel
Neural Guided Constraint Logic Programming for Program Synthesis [pdf] 
In Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018
- S. Casas, W. Luo and R. Urtasun
IntentNet: Learning to Predict Intention from Raw Sensor Data [pdf] 
In Conference on Robot Learning (CoRL), Zurich, Switzerland, October 2018
- A. Barsan, S. Wang, A. Pokrovsky and R. Urtasun
Learning to Localize Using a LiDAR Intensity Map [pdf] 
In Conference on Robot Learning (CoRL), Zurich, Switzerland, October 2018
- B. Yang, M. Liang and R. Urtasun
HDNET: Exploiting HD Maps for 3D Object Detection [pdf] 
In Conference on Robot Learning (CoRL), Zurich, Switzerland, October 2018
- M. Bai, G. Mattyus, N. Homayounfar, S. Wang, S. Kowshika Lakshmikanth and R. Urtasun
Deep Multi-Sensor Lane Detection [pdf] 
In International Conference on Intelligent Robots (IROS), Madrid, Spain, October 2018
- M. Liang, B. Yang, S. Wang and R. Urtasun
Deep Continuous Fusion for Multi-Sensor 3D Object Detection [pdf] 
In European Conference in Computer Vision (ECCV), Munich, Germanh, September 2018
- J. Liang and R. Urtasun
End-to-End Deep Structured Models for Drawing Crosswalks [pdf] 
In European Conference in Computer Vision (ECCV), Munich, Germanh, September 2018
- W. Ma, H. Chu, B. Zhou, R. Urtasun and A. Torralba
Single Image Intrinsic Decomposition Without a Single Intrinsic Image [pdf] 
In European Conference in Computer Vision (ECCV), Munich, Germanh, September 2018
- C. Zhang, W. Luo and R. Urtasun
Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds [pdf] 
In International Conference on 3D Vision (3DV), Verona, Italy, September 2018
- M. Teichmann, M. Weber, M. Zollner, R. Cipolla and R. Urtasun
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving [pdf]  (best poster award)
In Intelligent Vehicle Symposium (IV), Changshu, China, June 2018
- R. Liao, Y. Xiong, E. Fetaya, L. Zhang, K. Yoon, X. Pitkow, R. Urtasun and R. Zemel
Reviving and Improving Recurrent Back-Propagation [pdf]  (oral)
In International Conference in Machine Learning (ICML), Stockholm, Sweeden, July 2018
- M. Ren, W. Zeng, B. Yang and R. Urtasun
Learning to Reweight Examples for Robust Deep Learning [pdf]  (oral)
In International Conference in Machine Learning (ICML), Stockholm, Sweeden, July 2018
- W. Luo, B. Yang and R. Urtasun
Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- S. Wang, S. Suo, W.C. Ma, A. Pokrovsky and R. Urtasun
Deep Parametric Continuous Convolutional Neural Networks [pdf]  (spotlight)
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- M Ren, A. Pokrovsky, B. Yang and R. Urtasun
SBNet: Sparse Blocks Network for Fast Inference [pdf]  (spotlight)
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- D. Marcos, D. Tuia, B. Kellenberger, L. Zhang, M. Bai, R. Liao and R. Urtasun
Learning deep structured active contours end-to-end [pdf]  (spotlight)
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- B. Yang, W. Luo and R. Urtasun
PIXOR: Real-time 3D Object Detection from Point Clouds [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- N. Homayounfar, W. C. Ma, S. K. Lakshmikanth and R. Urtasun
Hierarchical Recurrent Attention Networks for Structured Online Maps [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- G. Mattyus and R. Urtasun
Matching Adversarial Networks [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- X. Qi, R. Liao, Z. Liu, R. Urtasun and J. Jia
GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation[pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- H. Chu, W.C. Ma, K. Kundu, R. Urtasun and S. Fidler
SurfConv: Bridging 3D and 2D Convolution for RGBD Images[pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, US, June 2018
- D. Frossard and R. Urtasun
End-To-End Learning of Multi-Sensor 3D Tracking by Detection[pdf] 
In International Conference on Robotics and Automation (ICRA), Brisbane, Australia, May 2018
2017
- A. Gomez, M. Ren, R. Urtasun and R. Grosse
The Reversible Residual Network: Backpropagation Without Storing Activations [pdf] 
In Neural Information Processing Systems (NIPS), Long Beach, California, December 2017
- E. Triantafillou, R. Zemel and R. Urtasun
Few-Shot Learning Through an Information Retrieval Lens [pdf] 
In Neural Information Processing Systems (NIPS), Long Beach, California, December 2017
- X. Qi, R. Liao, J. Ya, S. Fidler and R. Urtasun
3D Graph Neural Networks for RGBD Semantic Segmentation [pdf]  (oral)
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- B. Dai, D. Lin, R. Urtasun and S. Fidler
Towards Diverse and Natural Image Descriptions via a Conditional GAN [pdf]  (oral)
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- S. Wang, M. Bai, G. Mattyus, H. Chu, W. Luo, B. Yang, J. Liang, J. Cheverie, S. Fidler and R. Urtasun
TorontoCity: Seeing the World with a Million Eyes [pdf]  (spotlight)
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- S. Liu, J. Ya, S. Fidler and R. Urtasun
Sequential Grouping Networks for Instance Segmentation [pdf] 
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- S. Zhu, C. Loy, D. Ling, R. Urtasun and S. Fidler
Be Your Own Prada: Fashion Synthesis with Structural Coherence [pdf] 
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- R. Li, M. Tapaswi, R. Liao, J. Jia, R. Urtasun and S. Fidler
Situation Recognition with Graph Neural Networks [pdf] 
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- G. Mattyus, W. Luo and R. Urtasun
DeepRoadMapper: Extracting Road Topology from Aerial Images [pdf] 
In International Conference on Computer Vision (ICCV), Venice, Italy, October 2017
- N. Merkle, W. Luo, S. Auer, R. Muller and R. Urtasun
Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images [pdf] 
In Remote Sensing 2017
- M. Law, R. Urtasun and R. Zemel
Deep Spectral Clustering Learning [pdf]   (oral)
In Internatinal Conference in Machine Learning (ICML), Sydney, Australia, August 2017
- L. Castrejon, K. Kundu, R. Urtasun and S. Fidler
Annotating Object Instances with a Polygon-RNN [pdf]  (oral, best paper runner up award)
In Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, US, July 2017
- M. Bai and R. Urtasun
Deep Watershed Transform for Instance Segmentation [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, US, July 2017
- N. Homayounfar, S. Fidler and R. Urtasun
Sports Field Localization via Deep Structured Models [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, US, July 2017
- M. Law, Y. Yu, R. Urtasun, R. Zemel and E. Xing
Efficient Multiple Instance Metric Learning using Weakly Supervised Data [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, US, July 2017
- X. Chen, K. Kundu, Y. Zhu, H. Ma, S. Fidler and R. Urtasun
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection [pdf] 
In Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017
- M. Ren, R. Liao, R. Urtasun, F. H. Sinz and R. Zemel
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes [pdf] 
In International Conference on Learning Representations, (ICLR), Toulon, France, May 2017
- W. Ma, S. Wang, M. A. Brubaker, S. Fidler and R. Urtasun
Find Your Way
by Observing the Sun and Other Semantic Cues [pdf]
In International Conference on Robotics and Automation (ICRA), Singapore, May 2017
- W. Zeng, W. Luo, S. Fidler and R. Urtasun
Efficient Summarization with Read-Again and Copy Mechanism [pdf] 
In Arxiv preprint, arXiv:1611.03382, Nov 2016
- H. Chu, R. Urtasun and S. Fidler
Song From PI: A Musically Plausible Network for Pop Music Generation [pdf] 
In Arxiv preprint, arXiv:1611.03477, Nov 2016
2016
- S. Wang, S. Fidler and R. Urtasun
Proximal Deep Structured Models [pdf]
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016
- R. Liao, A. Schwing, R. Zemel and R. Urtasun
Learning Deep Parsimonious Representations [pdf]
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016
- W. Luo, Y. Li, R. Urtasun and R. Zemel
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks [pdf]
In Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016
- M. Bai, W. Luo, K. Kundu and R. Urtasun
Exploiting Semantic Information and Deep Matching for Optical Flow [pdf]  
In European Conference in Computer Vision (ECCV), Amsterdam, Netherlands, October 2016
- H. Chu, S. Wang, R. Urtasun and S. Fidler
HouseCraft: Building Houses from Rental Ads and Street Views [pdf]  
In European Conference in Computer Vision (ECCV), Amsterdam, Netherlands, October 2016
- T. Hazan, A. Schwing and R. Urtasun
Blending Learning and Inference in Conditional Random Fields [pdf]  
In Journal of Machine Learning Research (JMLR), 2016
- Y. Song, A. Schwing, R. Zemel and R. Urtasun
Training Deep Neural Networks via Direct Loss Minimization [pdf]   (oral)
In Internatinal Conference in Machine Learning (ICML), New York, US, June 2016
- W. Luo, A. Schwing and R. Urtasun
Efficient Deep Learning for Stereo Matching [pdf] [project/Code]  (spotlight)
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, US, June 2016
- M. Tapaswi, Y. Zhu, R. Stiefelhagen, R. Urtasun and S. Fidler
MovieQA: Understanding Stories in Movies through Question-Answering [pdf][Benchmark]  (spotlight)
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, US, June 2016
- G. Mattyus, S. Wang, S. Fidler and R. Urtasun
HD Maps: Fine-grained Road Segmentation by Parsing Ground and Aerial Images [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, US, June 2016
- X. Chen, K. Kundu, Z. Zhang, H. Ma, S. Fidler and R. Urtasun
Monocular 3D Object Detection for Autonomous Driving [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, US, June 2016
- Z. Zhang, S. Fidler and R. Urtasun
Instance-Level Segmentation with Deep Densely Connected MRFs [pdf] 
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, US, June 2016
- I. Vendov, R. Kiros, S. Fidler and R. Urtasun
Order-Embeddings of Images and Language [pdf]  (oral)
In International Conference on Learning Representations, (ICLR), San Juan, Puerto Rico, May 2016
- Y. Wang, M. Brubaker and R. Urtasun
Sequential Inference for Deep Gaussian Process [pdf] 
In International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, May 2016
- M. Brubaker, A. Geiger and R. Urtasun
Map-Based Probabilistic Visual Self-Localization [pdf] 
In Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2016
- R. Mottaghi, S. Fidler, A. Yuille, R. Urtasun and Devi Parikh
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding [pdf] 
In Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2016
2015
- P. Judd, J. Albericio, T. Hetherington, T. Aamodt, N. Enright Jerger R. Urtasun and A. Moshovos
Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets [pdf] 
In Arxiv preprint, arXiv:1511.05236, Nov 2015
- X. Chen, K. Kundu, Y. Zhu, A. Berneshawi, H. Ma, S. Fidler and R. Urtasun
3D Object Proposals for Accurate Object Class Detection [pdf] 
In Neural Information Processing Systems (NIPS), Montreal, Canada, December 2015
- R. Kiros, Y. Zhu, R. Salakhutdinov, R. Zemel, A. Torralba, R. Urtasun and S. Fidler
Skip-Thought Vectors [pdf][project/Code] 
In Neural Information Processing Systems (NIPS), Montreal, Canada, December 2015
- S. Wang, S. Fidler and R. Urtasun
Lost Shopping! Monocular Localization in Large Indoor Spaces [pdf]  (oral)
In International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015
- Y. Zhu, R. Kiros, R. Zemel, R. Salakhutdinov, R. Urtasun, A. Torralba and S. Fidler
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books [pdf][project page]  (oral)
In International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015
- G. Mattyus, S. Wang, S. Fidler and R. Urtasun
Enhancing World Maps by Parsing Aerial Images [pdf] 
In International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015
- P. Lenz, A. Geiger and R. Urtasun
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation [pdf] 
In International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015
- Z. Zhang, A. Schwing, S. Fidler and R. Urtasun
Monocular Object Instance Segmentation and Depth Ordering with CNNs [pdf] 
In International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Distributed Algorithms for Large Scale Learning and Inference in Graphical Models [pdf] 
In Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2015
- A. Schwing and R. Urtasun
Fully Connected Deep Structured Networks [pdf] 
In arXiv:1503.02351, March 2015
- D. Lin, C. Kong, S. Fidler and R. Urtasun
Generating Multi-Sentence Lingual Descriptions of Indoor Scenes [pdf]  (oral)
In British Machine Vision Conference (BMVC), Swansea, Wales, September 2015
- L. C. Chen, A. Schwing, A. Yuille and R. Urtasun
Learning Deep Structured Models [pdf]  (oral)
In International Conference on Machine Learning (ICML), Lille, France, July 2015
- S. Wang, S.Fidler and R. Urtasun
Holistic 3D Scene Understanding from a Single Geo-tagged Image [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- C. Liu, A. Schwing, K. Kundu, R. Urtasun and S.Fidler
Rent3D: Floor-Plan Priors for Monocular Layout Estimation [pdf]  (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- Y. Zhu, R. Urtasun, R. Salakhutdinov and S.Fidler
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- E. Simo, S. Fidler, F. Moreno-Noguer and R. Urtasun
Neuroaesthetics in Fashion: Modeling the Perception of Beauty [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- J. Xu, A. Schwing and R. Urtasun
Learning to Segment Under Various Weak Supervisions [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- J. Yao, M. Boben, S. Fidler and R. Urtasun
Real-Time Coarse-to-fine Topologically Preserving Segmentation [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, June 2015
- J. Yao, S. Ramalingam, Y. Taguchi, Y. Miki and R. Urtasun
Estimating Drivable Collision-Free Space from Monocular Video [pdf]
In Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, January 2015
2014
- S. Wang, A. Schwing and R. Urtasun
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials [pdf]
In Neural Information Processing Systems (NIPS), Montreal, Canada, December 2014
- J. Zhang, A. Schwing and R. Urtasun
Message Passing Inference for Large Scale Graphical Models with High Order Potentials [pdf]
In Neural Information Processing Systems (NIPS), Montreal, Canada, December 2014
- E. Simo, S. Fidler, F. Moreno-Noguer and R. Urtasun
A High Performance CRF Model for Clothes Parsing [pdf]
In Asian Conference on Computer Vision (ACCV), Singapore, November 2014
- K. Yamaguchi, D. McAllester and R. Urtasun
Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation [pdf][Project/Code]
In European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014
- Y. Wang, M Brubaker, B. Chaib-draa and R. Urtasun
Bayesian Filtering with Online Gaussian Process Latent Variable Models [pdf]
In Conference on Uncertainty in Artificial Intelligence (UAI), Quebec City, Canada, July 2014
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm [pdf]
In International Conference on Machine Learning (ICML), Beijing, China, June 2014
- C. Kong, D. Lin, M. Bansal, R. Urtasun and S. Fidler
What are you talking about? Text-to-Image Coreference [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- D. Lin, C. Kong, S. Fidler and R. Urtasun
Visual Semantic Search: Retrieving Videos via Complex Textual Queries [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- L-C Chen, S. Fidler, A. Yuille and R. Urtasun
Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- J. Xu, A. Schwing and R. Urtasun
Tell Me What You See and I will Show You Where It Is [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- R. Mottaghi, X Chen, X Liu, N. Cho, S. Lee, S. Fidler, R. Urtasun and A. Yuille
The Role of Context for Object Detection and Semantic Segmentation in the Wild [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- X. Chen, R. Mottaghi, X. Liu, S. Fidler, R. Urtasun and A. Yuille
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts[pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014
- S. Wang, L. Zhang and R. Urtasun
Transductive Gaussian Processes for Image Denoising[pdf]  (oral)
In International Conference on Computational Photography (ICCP), Santa Clara, California, May 2014
2013
- A. Geiger, M. Lauer, C. Wojek, C. Stiller and R. Urtasun.
3D Traffic Scene Understanding from Movable Platforms
In Pattern Analysis and Machine Intelligence (PAMI) 2013
- A. Geiger, P. Lenz, C. Stiller and R. Urtasun.
Vision meets Robotics: The KITTI Dataset
In International Journal of Robotics Research, (IJRR) 2013
- W. Luo, A. Schwing and R. Urtasun
Latent Structured Active Learning [pdf]
In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2013
- D. Lin, S. Fidler and R. Urtasun
Holistic Scene Understanding for 3D Object Detection with RGBD cameras [pdf]   (oral)
In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013
- A. Schwing, S. Fidler, M. Pollefeys and R. Urtasun
Box In the Box: Joint 3D Layout and Object Reasoning from Single Images [pdf]
In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013
- H. Zhang, A. Geiger and R. Urtasun
Understanding High-Level Semantics by Modeling Traffic Patterns [pdf]
In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013
- J. Zhang, K. Chen, A. Schwing and R. Urtasun
Estimating the 3D Layout of Indoor Scenes and its Clutter from Depth Sensors [pdf]
In International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013
- M. Brubaker, A. Geiger and R. Urtasun
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization [pdf]   (oral, Best Paper Runner up Award)
In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
- K. Yamaguchi, D. McAllester and R. Urtasun
Robust Monocular Epipolar Flow Estimation [pdf] (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
- S. Fidler, R. Mottaghi, A. Yuille and R. Urtasun
Bottom-up Segmentation for Top-down Detection [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
- S. Fidler, A. Sharma and R. Urtasun
A Sentence is Worth a Thousand Pixels [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
- R. Mottaghi, S. Fidler, J. Yao, R. Urtasun and D. Parikh
Analyzing Semantic Segmentation Using Human-Machine Hybrid CRFs [pdf]
In Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, June 2013
2012
- S. Fidler, S. Dickinson and R. Urtasun
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model
(spotlight)
In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2012
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins
In Neural Information Processing Systems (NIPS), Lake Tahoe, USA, December 2012
- K. Yamaguchi, T. Hazan, D. McAllester and R. Urtasun
Continuous Markov Random Fields for Robust Stereo Estimation
(oral)
In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012
- A. Schwing and R. Urtasun
Efficient Exact Inference for 3D Indoor Scene Understanding
In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012
- M. Salzmann and R. Urtasun
Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction
In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Efficient Structured Prediction with Latent Variables for General Graphical Models
(oral)
In International Conference on Machine Learning (ICML), Edimburgh, Scotland, June 2012
- A. Geiger, P. Lenz and R. Urtasun
Are we ready for autonomous driving? The KITTI Vision Benchmark Suite [pdf] [project page] (oral)
In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012
- J. Yao, S. Fidler and R. Urtasun
Describing the Scene as a Whole: Joint Object Detection, Scene Classification and Semantic Segmentation
In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Efficient Structured Prediction for 3D Indoor Scene Understanding
In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012
- A. Varol, M. Salzmann, P. Fua and R. Urtasun
A Constrained Latent Variable Model
In Conference on Computer Vision and Pattern Recognition (CVPR), Providence, USA, June 2012
- M. Brubaker, M. Salzmann and R. Urtasun
A Family of MCMC Methods on Implicitly Defined Manifolds
In International Conference on Artificial Intelligence and Statistics (AISTATS), Gran Canaria, Spain, April 2012
2011
- A. Geiger, C. Wojek and R. Urtasun
Joint 3D Estimation of Objects and Scene Layout
[pdf]
[supplementary]
[video]
In Neural Information Processing Systems (NIPS), Granada, Spain, December 2011
- A. Yao, J. Gall, L. van Gool and R. Urtasun
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities [pdf]
[video learning]
[video humaneva]
[software]
In Neural Information Processing Systems (NIPS), Granada, Spain, December 2011
- M. Salzmann and R. Urtasun
Physically-based Motion Models for 3D Tracking: A Convex Formulation
In International Conference on Computer Vision (ICCV), Barcelona, Spain, November 2011
- T. Hazan and R. Urtasun
Approximated Structured Prediction for Learning Large Scale
Graphical Models
Arxiv 1006.2899, June 2010
- J. Peng, T. Hazan, D. McAllester and R. Urtasun
Convex Max-Product over Compact Sets for Protein Folding (oral)
In International Conference in Machine Learning (ICML), Bellevue, Washington, June 2011
- A. Geiger, M. Lauer and R. Urtasun
A generative model for 3D urban scene understanding from movable platforms
[pdf]
[talk]
[slides]
[data]
[software] (oral)
In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011
- A. Schwing, T. Hazan, M. Pollefeys and R. Urtasun
Distributed Message Passing for Large Scale Graphical Models [pdf] [software]
In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011
- A. Shyr, T. Darrell, M. Jordan and R. Urtasun
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
In Conference of Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011
- H. Hamer, J. Gall, R. Urtasun and L. Van Gool
Data-Driven Animation of Hand- Object Interaction (oral)
In Face and Gesture Recognition (FGR), Santa Barbara, April 2011
2010
- A. Kapoor, K. Grauman, R. Urtasun and T. Darrell.
Gaussian Processes for Object Categorization
In International Journal in Computer Vision, (IJCV) 2010
- T. Hazan and R. Urtasun
A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
In Neural Information Processing Systems (NIPS), Vancouver, December 2010
- M. Salzmann and R. Urtasun
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
Inn Neural Information Processing Systems (NIPS), Vancouver, December 2010
- T. Kim, G. Shakhnarovich and R. Urtasun
Sparse coding for learning interpretable spatio-temporal primitivesIn Neural Information Processing Systems (NIPS), Vancouver, December 2010
- A. Geiger, M. Roser and R. Urtasun
Efficient Large-Scale Stereo Matching
[pdf] [talk] [software] (oral)
In Asian Conference in Computer Vision (ACCV), Queenstown, New Zealand, November 2010
- C. M. Christoudias, R. Urtasun, M. Salzmann and T. Darrell
Learning to Recognize Objects from Unseen Modalities
[pdf] [project page][software]
In European Conference in Computer Vision (ECCV), Crete, September 2010
- M. Salzmann and R. Urtasun
Combining Discriminative and Generative Methods for 3D Deformable Surface and Articulated Pose Reconstruction [pdf] [supplementary] (oral)
In Conference in Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010
- A. Shyr, R. Urtasun and M. I. Jordan
Sufficient Dimensionality Reduction for Visual Sequence Classification
In Conference in Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010
- M. Salzmann, C. Ek, R. Urtasun and T. Darrell
Factorized Orthogonal Latent Spaces
In International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy, May 2010
- M. Salzmann, C. H. Ek, R. Urtasun and T. Darrell
FOLS: Factorized Orthogonal Latent Spaces.
In Learning Workshop (Snowbird) Snowbird, Utah, April 2010
- M. Salzmann and R. Urtasun
A Constrained Combination of Discriminative and Generative Methods.
In Learning Workshop (Snowbird) Snowbird, Utah, April 2010
2009
- N. D. Lawrence and R. Urtasun
Non-linear Matrix Factorization with Gaussian Processes
[pdf] [software] (oral)
In International Conference in Machine Learning (ICML), Montreal June 2009
- A. Geiger, R. Urtasun and T. Darrell
Rank Priors for Continuous Non-Linear Dimensionality Reduction
[pdf] [video]
In Conference in Computer Vision and Pattern Recognition (CVPR), Miami June 2009
- C. M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell
Co-training with noisy perceptual observations
In Conference in Computer Vision and Pattern Recognition (CVPR), Miami June 2009
- C. M. Christoudias, R. Urtasun and T. Darrell
Bayesian Localized Multiple Kernel
Learning.
In Learning from Multiple Sources with Applications to Robotics Workshop at
NIPS, Whister, Canada, December 2009
- R. Urtasun
Non-Parametric Latent Variable Models for Shape and Motion Analysis.
Invited talk in MIRAGE
Versailles, France, May 2009
- N. D. Lawrence and R. Urtasun
Non-Linear Matrix Factorization.
In Learning Workshop (Snowbird)
Clearwater, Florida, April 2009
- R. Urtasun, A. Geiger and T. Darrell
Rank Priors for Continuous Non-Linear Dimensionality Reduction.
In Learning Workshop (Snowbird)
Clearwater, Florida, April 2009
- C. M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell
Co-training with Noisy Perceptual Observations.
In Learning Workshop (Snowbird)
Clearwater, Florida, April 2009
2008
- C. M. Christoudias, R. Urtasun and T. Darrell
Multi-View Learning in the Presence of View Disagreement
[pdf] [talk] (oral)
In Conference on Uncertainty in Artificial Intelligence (UAI) Helsinki, Finland, July 2008
- R. Urtasun, D. J. Fleet, A. Geiger, J. Popovic, T. Darrell and N. D. Lawrence.
Topologically-Constrained Latent Variable Models.
[pdf] [video] [talk] (oral)
In International Conference in Machine
Learning (ICML) Helsinki, Finland, July 2008
- R. Urtasun and
T. Darrell
Local Probabilistic Regression for Activity-Independent Human Pose Inference
In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008
- M. Salzmann, R. Urtasun and
P. Fua
Local Deformation Models for Monocular 3D Shape Recovery
(oral)
In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008
- C. M. Christoudias, R. Urtasun and
T. Darrell
Unsupervised Distributed Feature Selection for Multi-view Object Recognition
In Conference in Computer Vision and Pattern Recognition (CVPR) Anchorage, Alaska, June 2008
- R. Urtasun and T. Darrell
Local Probabilistic Regression for Activity-Independent Human Pose Inference.
In Learning Workshop (Snowbird)
Snowbird, Utah, April 2008
- R. Urtasun, A. Quattoni, N. D. Lawrence and T. Darrell
Transfering Nonlinear Representations using Gaussian Processes with a Shared Latent Space.
In Learning Workshop (Snowbird)
Snowbird, Utah, April 2008
-
R. Urtasun, A. Quattoni, N. Lawrence and T. Darrell
Transferring Nonlinear Representations using
Gaussian Processes with a Shared Latent Space
MIT technical report, 2008
2007
- A. Kapoor, K. Grauman, R. Urtasun and
T. Darrell
Active Learning with Gaussian Processes for Object Categorization
In International Conference in Computer Vision (ICCV) Rio de Janeiro, October 2007
- R. Urtasun and
T. Darrell
Discriminative
Gaussian Process Latent Variable Models for Classification (oral)
International Conference in Machine
Learning (ICML) Oregon, June 2007
- R. Urtasun, D. J. Fleet and N. D. Lawrence
Modeling human locomotion with topologically constrained latent variable models.
In ICCV Workshop on Human Motion: Understanding, Modeling, Capture and Animation,
Rio de Janeiro, Brazil, October 2007
2006
2005
2004
- R. Urtasun, P.
Glardon, R. Boulic, D. Thalmann and P. Fua.
Style-based
Motion Synthesis. [pdf] [video]
In Computer Graphics Forum (CGF),
Vol. 23, number 4 pp 799-812. December 2004
- R. Urtasun, P.
Fua.
3D
Human Body Tracking using Deterministic Motion Models.
In European Conference on Computer Vision (ECCV),
Prague, Czech Republic, May 2004
- L.Herda, R. Urtasun,
P. Fua.
Hierarchical
Implicit Surface Joint Limits to Constrain Video-Based
Motion Capture.
In European Conference on Computer Vision (ECCV),
Prague, Czech Republic, May 2004
- R. Urtasun, P.
Fua.
3D
Tracking for Gait Characterization and Recognition. (oral)
In Proceeding of the 6th International Conference
on Automatic Face and Gesture Recognition (FGR),
Seoul, Korea, May 2004. IEEE Computer Society.
-
R. Urtasun M. Salzmann and P. Fua
3D Morphing without User Interaction
EPFL technical report, 2004
2003
- L.Herda, R.Urtasun,
P.Fua, A.Hanson.
Automatic
Determination of Shoulder Joint Limits using Quaternion
Field Boundaries.
International Journal of Robotics Research (IJRR),
22(6): 419 - 436, 2003.
- P. Dokladal,
I. Bloch, M. Couprie, D. Ruijters, R. Urtasun
and L. Garnero.
Topologically
Controlled Segmentation of 3D Magnetic Resonance Images
of the Head by using Morphological Operators.
Pattern Recognition, 36(10):2463 - 2478, 2003.
2002
2001
2000
- R. Urtasun
Automatic segmentation
of a fix number of markers (apply to the cerebellum
and brainstem)
Telecom Paris technical report, 2000
- R. Urtasun
Segmentation of
a Guinea pig using mathematical morphology
Telecom Paris technical report, 2000
- R. Urtasun
Implementation
of a tool to Visualize Protocol Design and Processing
Eurecom's technical report, 2000
|
Prof. Raquel
Urtasun
Address:
Department of Computer Science
University of Toronto
6 King's College Rd
Toronto, Ontario, M5S 3G4
Canada
Phone: +1 (416) 946-8482
Email: urtasun (at) cs (dot) toronto (dot) edu
Fax: TBD
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