Projects sharing features with AttGAN Tensorflow

StarGAN is a PyTorch image-to-image translation framework designed to synthesize visual styles and attributes across multiple domains. It implements a generative adversarial network that serves as a deep learning image translator for modifying specific visual characteristics within an image dataset. The framework uses a single unified model to handle translations between multiple image domains rather than requiring separate pairs of models. It is a research implementation that learns mappings between different image attributes without the need for paired training data. The project covers the

pix2pix is a framework for image-to-image translation using conditional generative adversarial networks. It functions as a supervised trainer and visual domain mapper designed to learn a mapping between input and output images for style and domain transfer. The system utilizes a U-Net encoder-decoder architecture combined with a PatchGAN local discriminator to enforce high-frequency local consistency. It employs L1 loss regularization to ensure generated outputs remain structurally close to the ground truth. The project covers a broad range of computer vision capabilities, including semantic

Pytorch implementation

A simple interface for editing natural photos with generative neural networks.

Awesome-GANs is a curated resource list and research repository focused on the development and evaluation of generative adversarial networks. It serves as a structured index for academic literature and open-source implementations dedicated to the creation of synthetic data generators. The project provides a framework for training competing neural networks to produce outputs that mimic the statistical properties of original datasets. It emphasizes the use of configuration-driven pipelines to manage model hyperparameters and dataset paths, facilitating reproducible research workflows and standa

DeepFaceLab is a deep learning software suite designed for face swapping and the creation of deepfake videos. It functions as a neural network image compositor that replaces human faces or entire heads in video files to produce synthetic media. The tool provides capabilities for digital facial manipulation, including the ability to modify the perceived age of people in video sequences. It uses automated pattern recognition to blend source faces onto target frames to create seamless visual composites. The system covers a broad technical surface including landmark-based face alignment, autoenc

Primitive is an algorithmic art generator and geometric image reconstruction tool that transforms raster images into stylized vector compositions. It functions as an iterative shape optimizer and raster-to-vector converter, approximating pixel-based photos by layering geometric primitives such as triangles, circles, and rectangles. The project utilizes a search algorithm to determine the optimal position, size, and color for each shape to minimize the visual difference from the source image. Users can apply shape constraint definitions to control the properties and orientations of the geometr

This project is a deep learning style transfer framework designed to apply artistic styles to photographs. It functions as a photorealistic image stylizer that merges the content of one image with the visual characteristics of another while maintaining the original geometry and structural details. The system distinguishes itself through the use of matting Laplacian matrices and semantic segmentation masks to prevent distortion and preserve edge fidelity. These capabilities allow for region-specific styling, where different aesthetics can be applied to distinct objects or areas within a single

This project is a Stable Diffusion WebUI extension that provides a graphical interface for personalized portrait generation and AI photo editing. It allows users to train custom identity models from a small set of uploaded images to create consistent digital versions of specific people. The extension includes a virtual try-on system that replaces clothing in images by aligning reference garments with template bodies. It also features tools for face swapping in both static images and videos, as well as a portrait animator that transforms static images into dynamic videos using reference-guided

clmtrackr is a JavaScript computer vision library designed for facial landmark detection and real-time tracking. It implements Constrained Local Models to identify specific coordinate points on a human face within video feeds or static images. The project functions as a real-time face warping engine and expression analysis tool. It can distort facial images via parametric models to create caricatures or identify and label emotional states such as happiness, sadness, anger, and surprise based on feature coordinates. The library covers a broad range of capabilities including automatic and manu

IF is a text-to-image diffusion system that translates natural language descriptions into visual imagery. The project provides a generative pipeline for creating images, an inpainting tool for modifying specific image sections, and a super-resolution upscaler to increase pixel density and clarity. The system includes a concept fine-tuning framework that allows for the teaching of new visual concepts by updating a small set of parameters. It also supports image style transfer to apply the aesthetic characteristics of a reference image to a new output.

Code to reproduce results from the paper "AmbientGAN: Generative models from lossy measurements"

Three-dimensional content creation has been a central research area in computer graphics for decades. The main challenge is to minimize manual intervention, while still allowing the creation of a variety of plausible 3D objects. In this work, we present a global-to-local generative model to…

Boundary Equibilibrium Generative Adversarial Networks Implementation in Tensorflow

A list of all named GANs!

Official Pytorch Implementation of Residual Vision Transformers(ResViT) which is described in the following paper:

Official repository for ABC-GAN

dalle-mini is a text-to-image model and generative AI system designed to transform natural language descriptions into synthetic images. It functions as an image generation training toolkit and a generative model capable of creating visual representations from text prompts. The project provides a containerized deployment for consistent execution across different computing environments. It includes the necessary scripts and configuration files to train custom generative models from datasets. The system utilizes an autoregressive transformer architecture that treats visual data as discrete toke

This repository contains the source code for the CVPR oral paper Animating Arbitrary Objects via Deep Motion Transfer by Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov, Elisa Ricci and Nicu Sebe. We call the proposed deep framework Monkey-Net, as it enables motion transfer by…