FLT19940317's repositories
BasicSR
Basic Super-Resolution codes for development. Includes ESRGAN, SFT-GAN for training and testing.
Billion-scale-semi-supervised-learning
Implementing Billion-scale semi-supervised learning for image classification using Pytorch
BIQA_Toolbox
A benchmark implementation of representative deep BIQA models
blind_iqa_contrast
This repo compiles various blind image quality acessment methods focused on contrast evaluation. Only code that works in Python or Octave.
CMWTAT_Digital_Edition
CloudMoe Windows 10 Activation Toolkit get digital license, the best open source Win 10 activator in GitHub. GitHub 上最棒的开源 Win10 数字权利（数字许可证）激活工具！
DCNv2
Deformable Convolutional Networks v2 with Pytorch
entropic_image_contrast_measure
A novel measure of contrast in image based on entropy distribution of pixel color values. Very effective in measuring even subtle changes in exposure level of the same scene.
ffmpeg
学习音视频知识，整理资料，编写技术手册。
ffmpeg-python
Python bindings for FFmpeg - with complex filtering support
high-speed-downloader
百度网盘不限速下载 支持Windows和Mac 2018年1月16日更新
Image-Video-quality-assessments
Papers ondatabases and algorithms of image/video quality assessment
Learning-and-compression-for-big-datasets
This repos. contains simulation codes for joint learning and compression for big datasets
PolyU-Real-World-Noisy-Images-Dataset
Real-world Noisy Image Denoising: A New Benchmark
Pyramidbox.pytorch
Pyramidbox implement with pytorch
pytorch-deform-conv
PyTorch implementation of Deformable Convolution
pytorch-deform-conv-v2
PyTorch implementation of Deformable ConvNets v2 (Modulated Deformable Convolution)
RankIQA
The rep for the RankIQA paper in ICCV 2017
siti
Calculate Spatial Information / Temporal Information according to ITU-T P.910
The-Flask-Mega-Tutorial-zh
翻译自Miguel Grinberg的blog https://blog.miguelgrinberg.com 的2017年新版The Flask Mega-Tutorial教程
torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
vmaf
Perceptual video quality assessment based on multi-method fusion.
VSFA
Quality Assessment of In-the-Wild Videos, accepted by ACM MM 2019
VSR-DUF-Reimplement
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.
wdsr_ntire2018
Code of our winning entry to NTIRE 2018 super-resolution challenge. http://www.vision.ee.ethz.ch/ntire18/
YUView
The Free and Open Source Cross Platform YUV Viewer with an advanced analytics toolset