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Updated
Jun 1, 2024 - Python
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
Generate Art
This repository contains an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) trained on the FashionMNIST dataset. The project aims to generate realistic images of clothing items using a GAN architecture. It includes model definitions, training scripts, and visualizations of generated images at various training stages.
💻 🐈 Added a self-attention layer to the CycleGAN implementation (PyTorch).
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Welcome to the repository dedicated to exploring Generative Artificial Intelligence (AI) techniques in Computer Vision. This repository serves as a centralized hub for various projects, research, and resources related to generating visual content using AI models.
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