musque

pytorch-CycleGAN

对pytorch-CycleGAN使用中文命名重写

CycleGAN

Cycle-Consistent Unpaired Image-to-Image Translation Using PyTorch

CycleGAN-PyTorch

The simplest PyTorch implementation of CycleGAN.

cyclegans-demo

A demo of style transfers using CycleGAN image-to-image translation

CycleGAN_practice

图像风格迁移算法CycleGAN复现练习, 基于PyTorch

cycleGAN-PyTorch

A clean and lucid implementation of cycleGAN using PyTorch

simple_CycleGAN

a simplified pytorch CycleGAN implementation adapted from original code

CycleGANs-PyTorch

CycleGANs-PyTorch applied on Young to Old image converter.

MTCNN_face_detection_alignment

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

Face-Alignment

Face alignment with similarity transform based on MTCNN and RetinaFace.

Face_crop_align_mtcnn

Crop and Align Face by MTCNN

pix2pix

converting the sketch face image into real picture

Sketch-to-real-human-face-generator-iOS-Android-App

Sketch to real human face generator Android and iOS App

Sketch-Conversion---Final

We aim to convert sketches of face images to their photo realistic versions

face-sketch-to-photo-backend

SketchFooFE_AJS

This is the Front-End for the Sketch F00 Face Translation app.

sketch-to-face-translation

Sketch to face translation with GANs

sketch-to-face

Convert sketch to face image using Conditional Adversarial Nets (https://phillipi.github.io/pix2pix/)

face-sketch-interactivate

A project of face photo-sketch synthesis with Python which can change the synthesized sketch interactivitly.

sketch-to-face-gans

sketch-inverso

face sketch to photo conversion using cnn

Sketch-To-Face-Conversion-Using-GAN-For-Forensic-Research

face2sketch

DoodleNet

Convolutional Neural Network to convert crude sketches into faces

Auto_painter

Recently, realistic image generation using deep neural networks has become a hot topic in machine learning and computer vision. Such an image can be generated at pixel level by learning from a large collection of images. Learning to generate colorful cartoon images from black-and-white sketches is not only an interesting research problem, but also a useful application in digital entertainment. In this paper, we investigate the sketch-to-image synthesis problem by using conditional generative adversarial networks (cGAN). We propose a model called auto-painter which can automatically generate compatible colors given a sketch. Wasserstein distance is used in training cGAN to overcome model collapse and enable the model converged much better. The new model is not only capable of painting hand-draw sketch with compatible colors, but also allowing users to indicate preferred colors. Experimental results on different sketch datasets show that the auto-painter performs better than other existing image-to-image methods.

Image-Preprocessor

Face crop, sketch to edge detection and remove dots on sketches for further processing of CycleGAN

UniversalFPSS

Universal Face Photo-Sketch Style Transfer via Multiview Domain Translation

ConditionalGAN

Convert sketch to face image using Conditional Adversarial Nets (https://phillipi.github.io/pix2pix/)

Face-Sketch-to-Image-Generation-using-GAN

Face Sketch to Image Generation using Generative Adversarial Networks

SketchToFace

Pix2Pix Image translation using conditional generative adversarial network - sketch to face