facial-micro-expressiongc Goto Github PK

deep-image-prior-keras

Keras Implementation of Deep Image Prior paper for Super Resolution Upscaling

deep-learning-tutorial-pydata

Deep learning tutorial for PyData

deep-object-removal

Using cGANs to remove objects from a photo

deep_learning_for_biologists_with_keras

tutorials made for biologists to learn deep learning

deeplearningimplementations

Implementation of recent Deep Learning papers

depth-estimation

dfnet

Deep Fusion Network for Image Completion - ACMMM 2019

displacenet

Recognising Displaced People from Images by Exploiting Dominance Level - CVPR '19 Workshop on Computer Vision for Global Challenges (CV4GC)

ecnn

CNN to retrieve edge map of backround from a single scene with reflection.

edge-connect

EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212

face-aging

face-completion

Encoder-Decoder for Face Completion based on Gated Convolution

face-generator

face-skin-hair-segmentaiton-and-skin-color-evaluation

segmentation and color classification

face_aging

face_aging_with_cyclegan

face_gan

An adversarial translator for CelebA

face_generator

DCGAN face generator 🧑.

faceapp-with-deep-learning

facegan

Face completion using Generative Adversarial Networks

facegan-generating-random-faces

Generate Random Faces which do not exists. I trained a Deep Convolution GAN (DCGAN) on 100k celebrities photos.

facegenkerasvae

Generating faces using a variational autoencoder in Keras with Tensorflow

facelet_bank

Facelet-Bank for Fast Portrait Manipulation (pytorch)

fdpmnet

Fingerprint denoising using M-net based convolution neural network

fingerprint_denoising

fontgenerator

FontGenerator is an end-to-end system which generates handwritten characters with some font using conditional Generative Adversarial Network (C-GANs)

gan-keras

Generative Adversarial Network Implementations in Keras

gan-sandbox

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

gandissect

Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

ganotebooks

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch