Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN) of non-cuda user s and its also used by cuda user.
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Updated
Aug 10, 2018 - Python
Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN) of non-cuda user s and its also used by cuda user.
Generating imaginary facial images using DCGAN
Trained a Variational AutoEncoder Model to reconstruct the image and then sampled the latent space in order to get newly generated face images
Implementation of Perceptual Generative Autoencoders in PyTorch
PyTorch implementation of image inpainting technique as proposed in paper "Sementic Image Inpainting with Deep Generative Modes by R.A. Yeh et al."
Tensorflow keras GAN
In this project, I’ve used Generative Adversarial Networks (GANs) to generate new images of human faces from scratch, based on the neural networks being trained on real human faces. I used the MNIST dataset and CelebFaces Attributes (CelebA) dataset in this project.
DCGAN implementation using PyTorch
Example of use of nvidia dali
Face Generation using Adversarial Models
패치 기반 딥페이크 영상 검출에 관한 연구
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks" - (EASY to READ)
Vision&Perception project using GANs with CelebA dataset
Deep Learning for Computer Vision 2018 Spring
Face generation with DCGAN and SNGAN on CelebA dataset
This repository contains the code, models and corpus of the project "Generative Adversarial Networks for Text-to-Image Synthesis & Generation: A Comparative Analysis of Natural Language Processing models for the Spanish language".
A CNN used to fetch a person's identity based on their face.
A model with CycleGAN architecture for translating black & white images into colorized images
This repository inclused several applications of extracting and classifying features from face images.
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