Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Tensorflow implementation of the SRGAN algorithm for single image super-resolution

ImageNet pre-trained models with batch normalization for the Caffe framework

VggML (ICPR 2018, Beijing)

A program that can add an artistic touch to any image.

VGG16 Net implementation from PyTorch Examples scripts for ImageNet dataset

Multiclass image classification using Convolutional Neural Network

Neural Style implementation in PyTorch! 🎨

Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Generative Adversarial Network for single image super-resolution in high content screening microscopy images

Implementation of style transfer by tensorflow, for detail please see the paper "Image Style Transfer Using Convolutional Neural Networks"(CVPR2016)

The VGG16 and VGG19 networks in caffe with jupyter notebook

Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)

Implementation of the paper : Deep image analogy

Transferring the style of one image to the contents of another image, using PyTorch and VGG19.

Pre-trained VGG-Net Model for image classification using tensorflow

Fast and Accurate User constrained Thumbnail Generation using Adaptive Convolutions. | ICASSP 2019 [ORAL]

Optimal deep texture generation and style transfer based on Eric Risser's paper

Deepdream experiment implemented using Keras and VGG19 convnet