Segueix
Radu Timofte
Radu Timofte
Humboldt Professor for AI and Computer Vision, University of Würzburg
Correu electrònic verificat a uni-wuerzburg.de - Pàgina d'inici
Títol
Citada per
Citada per
Any
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
39552017
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
35912021
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
22272017
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
17852014
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
16222022
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
15992013
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
15212011
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
14652019
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
10732018
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
9682021
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
9042015
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
8002012
Probabilistic regression for visual tracking
M Danelljan, LV Gool, R Timofte
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
7312020
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
7202020
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
7172018
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
7032021
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
6782019
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
6752017
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
6652018
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
6302017
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
Articles 1–20