Image Super-Resolution Using Deep Convolutional Networks

Artículos que citan Image Super-Resolution Using Deep Convolutional Networks

Título / Autor	Año
Photo-realistic single image super-resolution using a generative adversarial network C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ... Proceedings of the IEEE conference on computer vision and pattern …	2017
Perceptual losses for real-time style transfer and super-resolution J Johnson, A Alahi, L Fei-Fei European conference on computer vision, 694-711	2016
Accurate image super-resolution using very deep convolutional networks J Kim, J Kwon Lee, K Mu Lee Proceedings of the IEEE conference on computer vision and pattern …	2016
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network W Shi, J Caballero, F Huszár, J Totz, AP Aitken, R Bishop, D Rueckert, ... Proceedings of the IEEE conference on computer vision and pattern …	2016
Deeply-recursive convolutional network for image super-resolution J Kim, J Kwon Lee, K Mu Lee Proceedings of the IEEE conference on computer vision and pattern …	2016
Accelerating the super-resolution convolutional neural network C Dong, CC Loy, X Tang European conference on computer vision, 391-407	2016
A survey of deep neural network architectures and their applications W Liu, Z Wang, X Liu, N Zeng, Y Liu, FE Alsaadi Neurocomputing 234, 11-26	2017
Recent advances in convolutional neural networks J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai, T Liu, X Wang, ... Pattern Recognition 77, 354-377	2018
Dehazenet: An end-to-end system for single image haze removal B Cai, X Xu, K Jia, C Qing, D Tao IEEE Transactions on Image Processing 25 (11), 5187-5198	2016
Deep laplacian pyramid networks for fast and accurate super-resolution WS Lai, JB Huang, N Ahuja, MH Yang Proceedings of the IEEE conference on computer vision and pattern …	2017
Deep networks for image super-resolution with sparse prior Z Wang, D Liu, J Yang, W Han, T Huang Proceedings of the IEEE international conference on computer vision, 370-378	2015
Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections X Mao, C Shen, YB Yang Advances in neural information processing systems, 2802-2810	2016
Unsupervised cross-domain image generation Y Taigman, A Polyak, L Wolf arXiv preprint arXiv:1611.02200	2016
Deep convolutional neural network for inverse problems in imaging KH Jin, MT McCann, E Froustey, M Unser IEEE Transactions on Image Processing 26 (9), 4509-4522	2017
Image super-resolution via deep recursive residual network Y Tai, J Yang, X Liu Proceedings of the IEEE conference on computer vision and pattern …	2017
Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification S Iizuka, E Simo-Serra, H Ishikawa ACM Transactions on Graphics (TOG) 35 (4), 110	2016
Deconvolution and checkerboard artifacts A Odena, V Dumoulin, C Olah Distill 1 (10), e3	2016
Learning deep CNN denoiser prior for image restoration K Zhang, W Zuo, S Gu, L Zhang Proceedings of the IEEE conference on computer vision and pattern …	2017
Compression artifacts reduction by a deep convolutional network C Dong, Y Deng, C Change Loy, X Tang Proceedings of the IEEE International Conference on Computer Vision, 576-584	2015
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

1 - 20

Las fechas y los recuentos de citas son estimados y se determinan de forma automática mediante un programa informático.