srcnn
There are 69 repositories under srcnn topic.
LoSealL/VideoSuperResolution
A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.
soapisnotfat/super-resolution
collection of super-resolution models & algorithms
yiyang7/Super_Resolution_with_CNNs_and_GANs
Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
thangvubk/video-super-resolution
Video super resolution implemented in Pytorch
kawaiibilli/pytorch_srcnn
pytorch implementation of Super Resolution CNN as discussed in http://personal.ie.cuhk.edu.hk/~ccloy/files/eccv_2014_deepresolution.pdf
Edwardlzy/SRCNN
Tensorflow implementation of single image super-resolution using a Convolutional Neural Network
YeongHyeon/Super-Resolution_CNN
Implementation of "Image Super-Resolution using Deep Convolutional Network"
TanakitInt/SRCNN-anime
A Super-Resolution Convolutional Neural Network builds for artwork, anime, and illustration. Senior Project - Artwork Enlargement and Quality Improvement using Machine Learning. ICITEE 2021 - Enhancement of Anime Imaging Enlargement Using Modified Super-Resolution CNN.
vilmacio/depixelate
Upscale an illustration and increase details
YeongHyeon/Super-Resolution_CNN-PyTorch
Implementation of 'Image Super-Resolution using Deep Convolutional Network'
george-gca/sr-pytorch-lightning
Super-Resolution models implemented in PyTorch Lightning
BobLiu20/SuperResolution_Caffe
Implementate super resolution in deep learning
jinsuyoo/srcnn
TensorFlow implementation of SRCNN
ashishpatel26/SRCNN_SRGAN_ESRGAN_ON_BRAIN_MRI
SRCNN_SRGAN_ESRGAN_ON_BRAIN_MRI
cicada5126/Image-quality-improvement-system-based-on-deep-learning
基于数字图像处理和深度学习的图像质量提升 使用PRIDNet 和SRCNN 进行去噪和超分. 用 SpringBoot+Mybatis plus+Vue进行界面和后端设计
Fivefold/SRCNN
Super Resolution Convolutional Neural Network (SRCNN) for Python/Torch, Numpy and Avnet's ZedBoard
meng1994412/SRCNN
Implemented super resolution convolutional neural networks (SRCNN) and applied super resolution to input images.
saadhaxxan/Image-Super-Resolution-with-SRCNN
Image-Super-Resolution-with-SRCNN
TheStarkor/SRCNN-tensorflow2
Implementation of SRCNN in Tensorflow 2
rageworx/SRCNN_OpenCV_GCC
C++ Implementation of Image Super-Resolution with Convolutional Neural Network with OpenCV adn OpenMP [Discontinued]
abdulwaheedsoudagar/SR-CNN
Super resolution based on SRCNN using Keras (2.0)
bloc97/Torch-VDSR
Torch implementation of the VDSR-CNN Upscaling algorithm
imironhead/ml_super_resolution
Replicated Results of Super Resolution Papers
Vaibhav-Rathod/Under-Water-Image-Enhancement-By-SRCNN
An underwater image enhancement method and a corresponding image super-resolution algorithm. Image enhancement Technique. Super-resolution Convolutional neural networks the Retinex algorithm gamma correction. Dark prior
Cuda-Chen/SRCNN-cpp
C++ implementation of SRCNN (Super-Resolution Convolutional Neural Network)
kcct-fujimotolab/keras-super-resolution
Easy model running super resolution based on SRCNN using Keras.
Nhat-Thanh/SRCNN-TF
Tensorflow 2.x based implementation of SRCNN for single image super-resolution
ryanhe312/waifu2x-qt
AI-powered Image Resize Tool
fbasatemur/SRCNN_Image_Restoration
Single image super resolution example has been tried to be created with Python/Keras and PyQt5
FilippoVajana/pytorch-SuperResolution
PyTorch implementation of SRCNN and EDSR neural networks for Super Resolution Single Frame tasks
khabiirk/SRCNN-webapp
A Flask and React webapp for a Super Resolution Convolutional Neural Network model.
Pol22/SuperResolutionCNN
SRCNN implementation described on https://arxiv.org/pdf/1501.00092.pdf
RakeshRaj97/EDSR-Super-Resolution
This repository is an implementation of EDSR model implemented in PyTorch
yukia18/srcnn-keras
SRCNN keras implementation
athiyadeviyani/super-resolution
Implementation of EDSR, ESPCN, LAPSRN, SRCNN, SRGAN and WDSR for single image super-resolution (SISR) based on Tensorflow 2.x for CMU's 10-707 Advanced Deep Learning Final Project
SaumyaBhandari/Image-SuperResolution-
A Super Sampling model created using the SRCNN method proposed by Chao Dong, Chen Change Loy in 2015. It uses Convolutional Networks to identify features and uses "Depth-To-Feature" technique in the end to generate a high resolution image of a given low resolution input. The model is trained and tested on BSDS500 dataset.