A set of tools for lexical and syntactical analysis written in pure PHP.
Welcome to Dissect!
master - this branch always contains the last stable version.
develop - the unstable development branch.
Dissect is a set of tools for lexical and syntactical analysis written in pure PHP.
Single Image Super-Resolution with EDSR, WDSR and SRGAN
A Tensorflow 2.x based implementation of
Enhanced Deep Residual Networks for Single Image Super-Resolution (EDSR), winner of the NTIRE 2017 super-resolution challenge.
ESRGAN (Enhanced SRGAN) [BasicSR] [EDVR] [DNI]
We have merged the training codes of ESRGAN into MMSR
MMSR is an open source image and video super-resolution toolbox based on PyTorch. It is a part of the open-
MMSR is an open source image and video super-resolution toolbox based on PyTorch. It is a part of the open-mmlab project developed by Multimedia Laboratory, CUHK. MMSR is based on our previous projects: BasicSR, ESRGAN, and
A modern PyTorch implementation of SRGAN
It is deeply based on Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network paper published by the Twitter team (https://arxiv.org/abs/1609.04
A Fully Progressive Approach to Single-Image Super-Resolution
Co-winner of the NTIRE Super-Resolution Challenge 2018
ProSR is a Single Image Super-Resolution (SISR) method designed upon the principle
We have merged BasicSR into MMSR
MMSR is an open source image and video super-resolution toolbox based on PyTorch. It is a part of the open-mmlab project developed by Multimedia Laboratory, CUHK. MMSR is based on our pr
A PyTorch implementation of the DSGAN and ESRGAN-FS models as described in the paper Frequency Separation for Real-World Super-Resolution. This work won the AIM 2019 challenge on Real-Wold Super-Resolution. For more information on the implementation visit the respective folders.
The goal of this repository is to enable real time super resolution for upsampling low resolution videos. Currently, the design follows the SR-GAN architecture. But instead of residual blocks, inverted residual blocks
Official implementation of Meta-SR: A Magnification-Arbitrary Network for Super-Resolution(CVPR2019)(PyTorch)
Our code is built on EDSR(PyTorch).
I find an error in my camera-ready, the PSNR
WARNING: A work in progress!
If you like this project, and you would like to have more plans and providers in the comparison, please take a look at this issue.
A comparison between some VPS providers t
A TensorFlow implementation of CVPR 2018 paper Residual Dense Network for Image Super-Resolution. Official implementation: Torch code for our CVPR 2018 paper "Residual Dense Network for Image Super-Resolution" (Spo
Arbitrary-scale super-resolution is a raising research topic with tremendous application potentials. Prior CNN-based SR approaches usually apply to only one fixed resolution scale, and thus unable to adjust their output dimension without changing the low-resolution input. Such design creates a huge gap between academic research and practical usage, and a majority of image up-sampling applications, even sensitive to precision, still heavily relied on bicubic interpolation despite its poor quality.
Everyone tries to implement a cache at some point in their app’s lifecycle, and this is ours. This is a library that allows people to cache NSData with time to live (TTL) values and semantics for disk management.
Super Mario World Widescreen is your beloved Mario World SNES game but in the 16:9 resolution. This is possible by expanding the horizontal resolution by 96 pixels, increasing resolution from 256x224 to 352x224. Since the original SNES does not have this resolution, the emulator focused into high definition mods bsnes-hd must be used.
Image Super-Resolution (ISR)
The goal of this project is to upscale and improve the quality of low resolution images.
This project contains Keras implementations of different Residual Dense Networks for Single Image Super-