Face generator

A Deep Convolutional Generative Adversarial Neural Networks to generate new images of faces

Udacity Deep Learning Nanodegree Face Generation PyTorch Project using DCGAN

GAN that can generate face images.

A DCGAN is trained on a dataset of faces. A generator network generates new images of faces that look very realistic.

This project is one of the projects required for Deep Learning Nanodegree

Face Generation - Udacity project for deep learning Nanodegree

Project for the module Generative Adversarial Networks for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

Face generation with deep convolutional generative adversarial network using PyTorch and Jupyter Notebook.

A game about smash or pass

Face Generation with DCGAN

High-Quality Face Morph Generation with Stable Diffusion

Udacity DLND final project . Use GAN generate face

This gan model trains itself from a given dataset of human faces and identifies each labels to generate new faces

A DCGAN in TensorFlow/Keras to generate artificial human faces, featuring an interactive web UI built with Streamlit for easy inference. This project was developed as part of a winter internship at IIT Guwahati.

Conditional Variational Autoencoder for generating 64×64 human faces with controllable attributes such as gender, glasses, and beard, trained on the CelebA dataset.

Official codebase for the paper "Synthetic Data for Fairness: Bias Mitigation in Facial Attribute Recognition" (IEEE, 2025). Includes an automated pipeline for generating, labeling, and evaluating synthetic facial datasets under demographic control using SD/GAN + fairness metrics.

Implementation of Perceptual Generative Autoencoders in PyTorch

A face generation model based on DCGAN architecture and WGAN-GP loss to prevent mode collapse