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Super Resolution

145 papers with code · Computer Vision

Super resolution is the task of taking an input of a low resolution (LR) and upscaling it to that of a high resolution.

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Greatest papers with code

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

CVPR 2017 tensorflow/models

The adversarial loss pushes our solution to the natural image manifold using a discriminator network that is trained to differentiate between the super-resolved images and original photo-realistic images.

IMAGE SUPER-RESOLUTION

Image Super-Resolution Using Deep Convolutional Networks

31 Dec 2014nagadomi/waifu2x

We further show that traditional sparse-coding-based SR methods can also be viewed as a deep convolutional network.

IMAGE SUPER-RESOLUTION VIDEO SUPER-RESOLUTION

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

1 Sep 2018xinntao/ESRGAN

To further enhance the visual quality, we thoroughly study three key components of SRGAN - network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN).

IMAGE SUPER-RESOLUTION

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

27 Mar 2016DmitryUlyanov/texture_nets

We consider image transformation problems, where an input image is transformed into an output image.

IMAGE SUPER-RESOLUTION STYLE TRANSFER

Deep Back-Projection Networks For Super-Resolution

CVPR 2018 thstkdgus35/EDSR-PyTorch

The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output.

IMAGE SUPER-RESOLUTION VIDEO SUPER-RESOLUTION

Enhanced Deep Residual Networks for Single Image Super-Resolution

10 Jul 2017thstkdgus35/EDSR-PyTorch

Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN).

IMAGE SUPER-RESOLUTION

A Fully Progressive Approach to Single-Image Super-Resolution

9 Apr 2018fperazzi/proSR

Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality.

IMAGE SUPER-RESOLUTION

cGANs with Projection Discriminator

ICLR 2018 pfnet-research/sngan_projection

We propose a novel, projection based way to incorporate the conditional information into the discriminator of GANs that respects the role of the conditional information in the underlining probabilistic model.

CONDITIONAL IMAGE GENERATION SUPER RESOLUTION