167 Open source projects that are alternatives of or similar to Deeply Recursive Cnn Tf

Matlab reimplementation of SCNSR

traiNNer: Deep learning framework for image and video super-resolution, restoration and image-to-image translation, for training and testing.

Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019) (PyTorch)

TensorFlow code for ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

Latest development of ISR/VSR. Papers and related resources, mainly state-of-the-art and novel works in ICCV, ECCV and CVPR about image super-resolution and video super-resolution.

Official TensorFlow code for paper "Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks".

A PyTorch implementation of SRGAN based on CVPR 2017 paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

A Real-ESRGAN model trained on a custom dataset

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

TensorRT Examples (TensorRT, Jetson Nano, Python, C++)

Code of our winning entry to NTIRE super-resolution challenge, CVPR 2018

Manual, source-code and binaries for the NanoJ-Fluidics project

Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination (CVPR, 2019)

Pytorch implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"

Keras Implementation of MIRNet - SoTA in Image Denoising, Super Resolution and Image Enhancement - CVPR 2020

Code repo for "Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution" (CVPRW NTIRE2020).

[TPAMI 2020] Parallax Attention for Unsupervised Stereo Correspondence Learning

Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)

SRZoo: An integrated repository for super-resolution using deep learning

Awesome Resources for Advanced Computer Vision Topics

NTIRE 2020 NonHomogeneous Dehazing Challenge (CVPR Workshop 2020) 1st Solution.

A Python implementation of RAISR

High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction

Official repository of JSI-GAN (Accepted at AAAI 2020).

Official repository of "Deep Coupled Feedback Network for Joint Exposure Fusion and Image Super-Resolution"

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.

Test Time Augmentation (TTA) wrapper for computer vision tasks: segmentation, classification, super-resolution, ... etc.

A video analysis tool built completely in python.

A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps

AI Super - Resolution

Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)

Official implementation of block state-based recursive network (BSRN) for super-resolution in TensorFlow

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, SRMD, RealSR, Anime4K, RIFE, CAIN, DAIN, and ACNet.

天池2019阿里巴巴优酷视频增强和超分辨率挑战赛自用代码，EDVR、WDSR、ESRGAN三个模型。

Coarse-to-Fine CNN for Image Super-Resolution (IEEE Transactions on Multimedia,2020)

Official repository of FISR (AAAI 2020).

Real-World Super-Resolution via Kernel Estimation and Noise Injection

Official Python implementation of the 'Sparse deconvolution'-v0.3.0

Implementation of 'Image Super-Resolution using Deep Convolutional Network'

Efficient & Generic Video Super-Resolution

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

ImSwitch is a software solution in Python that aims at generalizing microscope control by providing a solution for flexible control of multiple microscope modalities.

It is a re-implementation of paper named "Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation" called VSR-DUF model. There are both training codes and test codes about VSR-DUF based tensorflow.

Repository for "Light Field Spatial Super-resolution Using Deep Efficient Spatial-Angular Separable Convolution" , TIP 2018

VDSR (CVPR2016) pytorch implementation

Multi-frame super-resolution via sub-pixel.

Trainable models and NN optimization tools

AI无损放大工具

All image quality metrics you need in one package.

tf.image.resize_images has aliasing when downsampling and does not have gradients for bicubic mode. This implementation fixes those problems.

torch implementation of srgan

Pytorch implementation of Structure-Preserving Super Resolution with Gradient Guidance (CVPR 2020)

A Collection of Papers and Codes for ECCV2020 Low Level Vision or Image Reconstruction

Super-resolution (SR) is a method of creating images with higher resolution from a set of low resolution images.

3D super-resolution using Generative Adversarial Networks

Official implementation: Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

Real-time video quality improvement for applications such as video-chat using Perceptual Losses

Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"