Implementation of Perceptual Generative Autoencoders in PyTorch
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Updated
Jan 14, 2020 - Python
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."
DCGAN implementation using PyTorch
Face generation with DCGAN and SNGAN on CelebA dataset
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks" - (EASY to READ)
📷 This project presents functionality for applying medical masks to face images.
Feature selection | Neural Network with feedforward propagation and back propagation
Deep Learning for Computer Vision 2018 Spring
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".
Simple Tensorflow implementation of StarGAN (CVPR 2018 Oral)
[CVPR-2023] Re-thinking Model Inversion Attacks Against Deep Neural Networks
패치 기반 딥페이크 영상 검출에 관한 연구
Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN) of non-cuda user s and its also used by cuda user.
Tensorflow keras GAN
Face detection and feature extraction web app using CelebA dataset
A system for altering facial expressions in images using a Variational Autoencoder
Tensorflow implementation of StarGAN. Feature translation between images using Generative Adversarial Networks (GANs). It allows to modify a physical characteristic such as the hair color.
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