VeroHU

supervised_blur_kernel_estimation

If you have the original image and the blurred image, you can use this code to estimate the blur kernel.

verovero_perceptual_loss_for_SR

perceptual loss with keras: comparing the loss of features between generated and reference images. The features are extracted from VGG19.

Unet-of-remote-sensing-image

The semantic segmentation of remote sensing images

active_learning_breakingties

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

Bayesian_CNN

Bayes by Backprop implemented in a CNN

cvpr2019

cvpr2019 papers，极市团队整理

deep-image-prior

Image restoration with neural networks but without learning.

EnhanceNet-Code

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis (official repository)

FSRNet

Demo code for our CVPR'18 paper "FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors" (SPOTLIGHT Presentation)

GRE

GRE备考资料分享

SFTGAN

CVPR18 - Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform

TOFEL_IELTS_GRE_my-Learning-materials-

托福雅思GRE和GMAT资料

unet

unet for image segmentation

VeroHU

Config files for my GitHub profile.

wdsr

Keras-based implementation of WDSR and EDSR for single image super-resolution

ZF_UNET_224_Pretrained_Model

Modification of convolutional neural net "UNET" for image segmentation in Keras framework

ZSSR

"Zero-Shot" Super-Resolution using Deep Internal Learning