啦啦啦啦啦's repositories
BMSG-GAN
[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning.
CDAN
Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)
deep-learning-models
Keras code and weights files for popular deep learning models.
deeplearning-models
A collection of various deep learning architectures, models, and tips
dehaze_underwater_image
dehaze_underwater_image
Delving-deep-into-GANs
A curated list of Generative Adversarial Networks (GANs) resources sorted by reputation
GFN-dehazing
Gated Fusion Network for Single Image Dehazing
hello-world
my first contribute to github
Image-Quality-Assessment-Benchmark
A collection of state-of-the-art image quality assessment algorithms
ImageEnhanceViaFusion
It is a Java implementation of underwater images and videos enhancement by fusion
leeml-notes
李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes
LeetCodeAnimation
Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）
OptimizedImageEnhance
Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc.
perceptual-reflection-removal
Single Image Reflection Separation with Perceptual Losses
Python_Notes
study notes, practise and projects codes
Single-Underwater-Image-Enhancement-and-Color-Restoration
Single Underwater Image Enhancement and Color Restoration
spider
learning
UCIQE
Underwater Color Image Quality Evaluation
UnderWater
Companion repository to the paper Automatic Red-Channel Underwater Image Restoration, by Galdran et al.
underwater-hl
MATLAB code for color restoration of underwater images
Underwater-Image-Enhancement-by-Wavelength-Compensation-and-Dehazing
ACQUIRING clear images in underwater environments is an important issue in ocean engineering. The quality of underwater images plays a pivotal role in scientific missions such as monitoring sea life, taking census of populations, and assessing geological or biological environments. Capturing images underwater is challenging, mostly due to haze caused by light that is reflected from a surface and is deflected and scattered by water particles, and colour change due to varying degrees of light attenuation for different wavelengths. Light scattering and colour change result in contrast loss and colour deviation in images acquired underwater.
Underwater-image-restoration
Implementation of Chongyi Li et.al algorithm for underwater image restoration.
VCIP2017
VCIP 2017 : Visual Communications and Image Processing