518 papers with code • 0 benchmarks • 19 datasets

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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( Credit: MemNet )

Greatest papers with code

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

tensorflow/models CVPR 2017

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

nagadomi/waifu2x 31 Dec 2014

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

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

alexjc/neural-enhance 27 Mar 2016

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

Image Super-Resolution Nuclear Segmentation +2

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

eriklindernoren/PyTorch-GAN 1 Sep 2018

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).

Face Hallucination Image Super-Resolution

Deep Image Prior

DmitryUlyanov/deep-image-prior CVPR 2018

In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning.

Image Denoising Image Inpainting +3

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

adamian98/pulse CVPR 2020

We present an algorithm addressing this problem, PULSE (Photo Upsampling via Latent Space Exploration), which generates high-resolution, realistic images at resolutions previously unseen in the literature.

Face Hallucination Image Super-Resolution

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

thunil/TecoGAN 23 Nov 2018

Additionally, we propose a first set of metrics to quantitatively evaluate the accuracy as well as the perceptual quality of the temporal evolution.

Image Super-Resolution Motion Compensation +2

Residual Dense Network for Image Super-Resolution

idealo/image-super-resolution CVPR 2018

In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers.

Color Image Denoising Image Super-Resolution

SinGAN: Learning a Generative Model from a Single Natural Image

tamarott/SinGAN ICCV 2019

We introduce SinGAN, an unconditional generative model that can be learned from a single natural image.

Image Generation Image Manipulation +1