Seguir
Radu Timofte
Radu Timofte
Humboldt Professor for AI and Computer Vision, University of Würzburg
Dirección de correo verificada de uni-wuerzburg.de - Página principal
Título
Citado por
Citado por
Año
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
30692017
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
21622021
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
17102014
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
16362017
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
14992013
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
12962011
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
11652019
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
9612018
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
8462022
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
8142015
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
7912012
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
6552021
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
5962018
Probabilistic regression for visual tracking
M Danelljan, LV Gool, R Timofte
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
5862020
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
5742018
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
5732017
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
5702019
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
5552020
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
5402017
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
5242018
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20