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Areas Served: GANs (Generative Adversarial Networks:)
Author(s): Data Science meets Cyber Security Originally published on Towards AI. We Saw the Generative AI, Now Let’s See How Actually It Is Generated.! IMAGE SOURCE: BY AUTHOR INTRODUCTION: GANs, Generative Adversarial networks, let’s first understand what GANs are. So I have …
GANsformers: Generate complex scenes using GANs and Transformers
Author(s): Louis Bouchard Originally published on Towards AI. They basically leverage transformers’ attention mechanism in the powerful StyleGAN2 architecture to make it even more powerful! Results examples on generating bedroom scenes with its attention maps. Image from: Drew A. Hudson and C. …
Manipulate Images with Blobs! BlobGAN Explained
Author(s): Louis Bouchard Originally published on Towards AI. A GAN model that uses simple blobs to manipulate objects in images… Originally published on louisbouchard.ai, read it 2 days before on my blog! If you think that the progress with GANs was over, …
A Beginner’s Guide to Building a Conditional GAN.
Author(s): Pere Martra Originally published on Towards AI. A comprehensive guide to creating conditional GANs with TensorFlow, Python and Keras for imaging generation. Image generated by author using Dall.E 2 A GAN can be used to make images similar to those of …
![Building and Deploying a GAN Streamlit Web App on Heroku [Part 2]](https://miro.medium.com/v2/resize:fit:875/1*cYHuPy24V-HyPV56PnX28A.png)
Building and Deploying a GAN Streamlit Web App on Heroku [Part 2]
Author(s): Youssef Hosni Originally published on Towards AI. Table of Contents: One of the most fascinating applications of AI is in the field of image generation, which has been made possible by the development of Generative Adversarial Networks (GANs). In this article, …
Image Manipulation with Your Mouse! Drag Your Gan Explained
Author(s): Louis Bouchard Originally published on Towards AI. Drag anything from point A to point B Originally published on louisbouchard.ai, read it 2 days before on my blog! https://www.youtube.com/embed/r1mh-IqBEjg If you thought generating new images was cool, or editing them with some …
Diffusion Models vs. GANs vs. VAEs: Comparison of Deep Generative Models
Author(s): Ainur Gainetdinov Originally published on Towards AI. Diffusion Models vs. GANs vs. VAEs: Comparison of Deep Generative Models Deep generative models are applied to diverse domains such as image, audio, video synthesis, and natural language processing. With the rapid development of …
Efficient Strategies for Effective Stable Diffusion Prompt: A Comprehensive Guide
Author(s): Youssef Hosni Originally published on Towards AI. Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, which is known as prompt. Developing a process to build good prompts is the first step every …
How To Use TPUs in Kaggle / Google Colab To Train a GAN in the Blink of An Eye.
Author(s): Pere Martra Originally published on Towards AI. Looking to speed up your GAN training? In this article, I’ll show you how to utilize TPUs in Kaggle or Google Colab to drastically reduce training time, allowing you to generate high-quality images in …
GAN Mode Collapse Explanation
Author(s): Ainur Gainetdinov Originally published on Towards AI. A detailed analysis of the causes of mode collapse. Generative Adversarial Networks (GANs) are a type of deep learning model that has gained a lot of attention in recent years due to their ability …
How to make a GAN to generate color images.
Author(s): Pere Martra Originally published on Towards AI. In this article, we continue our journey through the exciting world of GANs and learn how Generative AI works with a Color Dataset. Image generated by Author using Dall-E-2 In the first article, we …
Understanding GANs
Author(s): Shweta Baranwal Originally published on Towards AI. Photo from https://wallpaperaccess.com/ Deep Learning GANs (Generative Adversarial Networks) are a class of models where images are translated from one distribution to another. GANs are helpful in various use-cases, for example: enhancing image quality, …
Techniques in Self-Attention Generative Adversarial Networks
Author(s): Sherwin Chen Originally published on Towards AI. Self Attention GAN (SAGAN) U+007C Towards AI Discussion about different approaches of SAGAN like spectral normalization, conditional batch normalization, etc. Image generated by my implementation of SAGAN on celebA dataset after 120k iterations Introduction …
Introduction
Author(s): Manish Nayak Originally published on Towards AI. An Introduction to Pix2Pix cGANs U+007C Towards AI Pix2Pix Network, An Image-To-Image Translation Using Conditional GANs (cGANs) Pix2Pix network is basically a Conditional GANs (cGAN) that learn the mapping from an input image to …
Face Aging Using Conditional GANs
Author(s): Manish Nayak Originally published on Towards AI. Age-cGANs Explained U+007C Towards AI An Introduction to Age-cGANs Introduction Conditional GANs (CGANs) are extensions of the GANs model. You can read about Conditional GANs in my previous post here. In this post, I …
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