| 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 | 3703 | 2017 |
| SwinIR: Image restoration using swin transformer J Liang, J Cao, G Sun, K Zhang, L Van Gool, R Timofte ICCV Workshops; code: https://github.com/JingyunLiang/SwinIR, 2021 | 3190 | 2021 |
| 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 | 2131 | 2017 |
| 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 | 1766 | 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 | 1572 | 2013 |
| 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 | 1460 | 2011 |
| Repaint: Inpainting using denoising diffusion probabilistic models A Lugmayr, M Danelljan, A Romero, F Yu, R Timofte, L Van Gool Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 1393 | 2022 |
| Learning discriminative model prediction for tracking G Bhat, M Danelljan, LV Gool, R Timofte Proceedings of the IEEE International Conference on Computer Vision, 6182-6191, 2019 | 1389 | 2019 |
| 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 | 1047 | 2018 |
| 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 | 879 | 2015 |
| Plug-and-play image restoration with deep denoiser prior K Zhang, Y Li, W Zuo, L Zhang, L Van Gool, R Timofte IEEE TPAMI, code: https://github.com/cszn/DPIR, 2021 | 871 | 2021 |
| 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 | 797 | 2012 |
| Probabilistic regression for visual tracking M Danelljan, LV Gool, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 695 | 2020 |
| Deep unfolding network for image super-resolution K Zhang, L Van Gool, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 681 | 2020 |
| O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images CO Ancuti, C Ancuti, R Timofte, C De Vleeschouwer Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 675 | 2018 |
| 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 | 649 | 2017 |
| 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 | 646 | 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 | 639 | 2019 |
| Designing a practical degradation model for deep blind image super-resolution K Zhang, J Liang, L Van Gool, R Timofte ICCV 2021; arXiv preprint arXiv:2103.14006, 2021 | 628 | 2021 |
| 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 | 608 | 2017 |
Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEEmail verificata su insait.ai