| 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 | 11042 | 2012 |
| Vision meets Robotics: The KITTI Dataset A Geiger, P Lenz, C Stiller, R Urtasun IJRR, 2013 | 6968 | 2013 |
| Skip-thought vectors R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ... Advances in neural information processing systems 28, 2015 | 2774 | 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 | 2201 | 2015 |
| Understanding the effective receptive field in deep convolutional neural networks W Luo, Y Li, R Urtasun, R Zemel Advances in neural information processing systems 29, 2016 | 1380 | 2016 |
| 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 | 1259 | 2014 |
| Learning to reweight examples for robust deep learning M Ren, W Zeng, B Yang, R Urtasun International conference on machine learning, 4334-4343, 2018 | 1104 | 2018 |
| Efficient large-scale stereo matching A Geiger, M Roser, R Urtasun Computer Vision–ACCV 2010, 25-38, 2010 | 1023 | 2010 |
| 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 | 946 | 2018 |
| 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 | 894 | 2016 |
| 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 28, 2015 | 837 | 2015 |
| Efficient deep learning for stereo matching W Luo, AG Schwing, R Urtasun Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 813 | 2016 |
| Deep continuous fusion for multi-sensor 3d object detection M Liang, B Yang, S Wang, R Urtasun Proceedings of the European conference on computer vision (ECCV), 641-656, 2018 | 699 | 2018 |
| 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 | 651 | 2018 |
| 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 | 632 | 2016 |
| Deep watershed transform for instance segmentation M Bai, R Urtasun Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 573 | 2017 |
| 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 | 571 | 2006 |
| Towards diverse and natural image descriptions via a conditional gan B Dai, S Fidler, R Urtasun, D Lin Proceedings of the IEEE international conference on computer vision, 2970-2979, 2017 | 568 | 2017 |
| Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net W Luo, B Yang, R Urtasun Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018 | 566 | 2018 |
| 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 | 546 | 2014 |
Sanja FidlerUniversity of Toronto, NVIDIA在 cs.toronto.edu 的電子郵件地址已通過驗證
