| Are we ready for autonomous driving? the kitti vision benchmark suite A Geiger, P Lenz, R Urtasun 2012 IEEE Conference on Computer Vision and Pattern Recognition, 3354-3361, 2012 | 6279 | 2012 |
| Vision meets Robotics: The KITTI Dataset A Geiger, P Lenz, C Stiller, R Urtasun IJRR, 2013 | 3826 | 2013 |
| Skip-thought vectors R Kiros, Y Zhu, R Salakhutdinov, RS Zemel, A Torralba, R Urtasun, ... arXiv preprint arXiv:1506.06726, 2015 | 2067 | 2015 |
| Aligning books and movies: Towards story-like visual explanations by watching movies and reading books Y Zhu, R Kiros, R Zemel, R Salakhutdinov, R Urtasun, A Torralba, S Fidler Proceedings of the IEEE international conference on computer vision, 19-27, 2015 | 925 | 2015 |
| Gaussian process dynamical models for human motion JM Wang, DJ Fleet, A Hertzmann IEEE transactions on pattern analysis and machine intelligence 30 (2), 283-298, 2007 | 885 | 2007 |
| Efficient large-scale stereo matching A Geiger, M Roser, R Urtasun Computer Vision–ACCV 2010, 25-38, 2010 | 868 | 2010 |
| The role of context for object detection and semantic segmentation in the wild R Mottaghi, X Chen, X Liu, NG Cho, SW Lee, S Fidler, R Urtasun, A Yuille Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 790 | 2014 |
| Understanding the effective receptive field in deep convolutional neural networks W Luo, Y Li, R Urtasun, R Zemel arXiv preprint arXiv:1701.04128, 2017 | 596 | 2017 |
| Efficient deep learning for stereo matching W Luo, AG Schwing, R Urtasun Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 560 | 2016 |
| 3D people tracking with Gaussian process dynamical models R Urtasun, DJ Fleet, P Fua 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 538 | 2006 |
| 3d object proposals for accurate object class detection X Chen, K Kundu, Y Zhu, AG Berneshawi, H Ma, S Fidler, R Urtasun Advances in Neural Information Processing Systems, 424-432, 2015 | 523 | 2015 |
| Monocular 3d object detection for autonomous driving X Chen, K Kundu, Z Zhang, H Ma, S Fidler, R Urtasun Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 492 | 2016 |
| Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation J Yao, S Fidler, R Urtasun 2012 IEEE conference on computer vision and pattern recognition, 702-709, 2012 | 451 | 2012 |
| Multinet: Real-time joint semantic reasoning for autonomous driving M Teichmann, M Weber, M Zoellner, R Cipolla, R Urtasun 2018 IEEE Intelligent Vehicles Symposium (IV), 1013-1020, 2018 | 415 | 2018 |
| 3d traffic scene understanding from movable platforms A Geiger, M Lauer, C Wojek, C Stiller, R Urtasun IEEE transactions on pattern analysis and machine intelligence 36 (5), 1012-1025, 2013 | 403 | 2013 |
| Learning to reweight examples for robust deep learning M Ren, W Zeng, B Yang, R Urtasun International Conference on Machine Learning, 4334-4343, 2018 | 385 | 2018 |
| Order-embeddings of images and language I Vendrov, R Kiros, S Fidler, R Urtasun arXiv preprint arXiv:1511.06361, 2015 | 385 | 2015 |
| Movieqa: Understanding stories in movies through question-answering M Tapaswi, Y Zhu, R Stiefelhagen, A Torralba, R Urtasun, S Fidler Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 383 | 2016 |
| Detect what you can: Detecting and representing objects using holistic models and body parts X Chen, R Mottaghi, X Liu, S Fidler, R Urtasun, A Yuille Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 376 | 2014 |
| Pixor: Real-time 3d object detection from point clouds B Yang, W Luo, R Urtasun Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 373 | 2018 |
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
