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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)

d2l-zh

《动手学深度学习》

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

test learning git

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

uiqm

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