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cuiwenxue's Projects

bimef icon bimef

Code and data for the research paper "A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement" (Submitted to IEEE Transactions on Cybernetics)

cbdnet icon cbdnet

Code for "Toward Convolutional Blind Denoising of Real Photographs"

cross-domain-detection icon cross-domain-detection

Codes and datasets for 'Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation' [Inoue+, CVPR2018].

csquantization icon csquantization

Research code repository for ongoing development of methods connecting quantization and compressed sensing.

dcpdn icon dcpdn

Densely Connected Pyramid Dehazing Network (CVPR'2018)

deblurgan icon deblurgan

Image Deblurring using Generative Adversarial Networks

dehazenet icon dehazenet

DehazeNet: An End-to-End System for Single Image Haze Removal

did-mdn icon did-mdn

Density-aware Single Image De-raining using a Multi-stream Dense Network (CVPR 2018)

dncnn-pytorch icon dncnn-pytorch

PyTorch implementation of the TIP2017 paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising"

dncnn-tensorflow icon dncnn-tensorflow

:octocat::octocat:A tensorflow implement of the paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising"

drrn-pytorch icon drrn-pytorch

An implementation of Deep Recursive Residual Network for Super Resolution (DRRN), CVPR 2017

drrn_cvpr17 icon drrn_cvpr17

Code for our CVPR'17 paper "Image Super-Resolution via Deep Recursive Residual Network"

espcn icon espcn

A PyTorch implementation of ESPCN based on CVPR2016 paper "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network"

gan-compression icon gan-compression

This repository contains the source for the paper "Analysing Image Compression using Generative Adversarial Networks"

generative-compression icon generative-compression

TensorFlow Implementation of Generative Adversarial Networks for Extreme Learned Image Compression

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