| A+: Adjusted anchored neighborhood regression for fast super-resolution R Timofte, V De Smet, L Van Gool Asian conference on computer vision, 111-126, 2014 | 1147 | 2014 |
| Anchored neighborhood regression for fast example-based super-resolution R Timofte, V De Smet, L Van Gool Proceedings of the IEEE international conference on computer vision, 1920-1927, 2013 | 1043 | 2013 |
| NTIRE 2017 challenge on single image super-resolution: Dataset and study E Agustsson, R Timofte Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 717 | 2017 |
| Pedestrian detection at 100 frames per second R Benenson, M Mathias, R Timofte, L Van Gool 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2903-2910, 2012 | 713 | 2012 |
| The German traffic sign recognition benchmark: a multi-class classification competition J Stallkamp, M Schlipsing, J Salmen, C Igel The 2011 international joint conference on neural networks, 1453-1460, 2011 | 626 | 2011 |
| NTIRE 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 592 | 2017 |
| Deep expectation of real and apparent age from a single image without facial landmarks R Rothe, R Timofte, L Van Gool International Journal of Computer Vision (IJCV), 2018 | 461 | 2018 |
| Hough transform and 3D SURF for robust three dimensional classification J Knopp, M Prasad, G Willems, R Timofte, L Van Gool European Conference on Computer Vision, 589-602, 2010 | 403 | 2010 |
| Dex: Deep expectation of apparent age from a single image R Rothe, R Timofte, L Van Gool Proceedings of the IEEE international conference on computer vision …, 2015 | 400 | 2015 |
| Multi-view traffic sign detection, recognition, and 3D localisation R Timofte, K Zimmermann, L Van Gool Machine vision and applications 25 (3), 633-647, 2014 | 349 | 2014 |
| Multi-view traffic sign detection, recognition, and 3d localisation R Timofte, K Zimmermann, L Van Gool IEEE Workshop on Applications of Computer Vision (WACV), 2009 | 349* | 2009 |
| Seven ways to improve example-based single image super resolution R Timofte, R Rothe, L Van Gool Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 301 | 2016 |
| Traffic sign recognition—How far are we from the solution? M Mathias, R Timofte, R Benenson, L Van Gool The 2013 international joint conference on Neural networks (IJCNN), 1-8, 2013 | 300 | 2013 |
| Soft-to-hard vector quantization for end-to-end learning compressible representations E Agustsson, F Mentzer, M Tschannen, L Cavigelli, R Timofte, L Benini, ... Advances in Neural Information Processing Systems, 1141-1151, 2017 | 224 | 2017 |
| Fast optical flow using dense inverse search T Kroeger, R Timofte, D Dai, L Van Gool European Conference on Computer Vision, 471-488, 2016 | 201 | 2016 |
| Conditional probability models for deep image compression F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 193 | 2018 |
| The 2018 pirm challenge on perceptual image super-resolution Y Blau, R Mechrez, R Timofte, T Michaeli, L Zelnik-Manor Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018 | 186 | 2018 |
| Generative adversarial networks for extreme learned image compression E Agustsson, M Tschannen, F Mentzer, R Timofte, LV Gool Proceedings of the IEEE/CVF International Conference on Computer Vision, 221-231, 2019 | 184 | 2019 |
| DSLR-quality photos on mobile devices with deep convolutional networks A Ignatov, N Kobyshev, R Timofte, K Vanhoey, L Van Gool Proceedings of the IEEE International Conference on Computer Vision, 3277-3285, 2017 | 182 | 2017 |
| AI Benchmark: Running deep neural networks on android smartphones A Ignatov, R Timofte, W Chou, K Wang, M Wu, T Hartley, L Van Gool Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018 | 165 | 2018 |
Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHVerified email at ethz.ch
