This project requires you to use image processing techniques to create a color image from the digitized Prokudin-Gorskii glass plate photographs, with the goal of producing an image with as few visual artifacts as possible. A digital picture of a glass plate, with its three channels arranged from top to bottom as BGR, serves as the process’s input. Our task is to isolate the three channels and properly align them.

In this project, we first attempted to reproduce and explore the GigaGAN model, uncovering its remarkable text-to-image processing techniques. Subsequently, we shifted our focus to the MinImagen2 architecture, an efficient text-to-image generation model capable of producing high-quality images. Our goal is to experiment with these two models, comparing their strengths and weaknesses, and ultimately share our findings and experiences in the world of image generation.

In this project, we explore the applications of Generative Adversarial Networks (GANs) for photo editing tasks such as image reconstruction, interpolation, and synthesis.

Welcome to our website about Gradient Domain Fusion, a powerful technique that allows for seamless merging of multiple images into a single high-quality output. Our project aims to explore this technique and provide a detailed guide on how to implement it effectively.

I’m excited to share my recent project on Neural Style Transfer, which is a fascinating technique that combines the content of one image with the artistic style of another, resulting in a stunning and unique blend of the two.