Text-To-Image-And-Video Generator Using Machine Learning

Abstract

The innovative idea about Text-to-Image and Video Synthesis Applications utilising state-of-the-art machine learning techniques. The primary aim is to seamlessly generate realistic visual content from textual descriptions, bridging the gap between language and multimedia. The application showcases its proficiency in generating convincing images of birds and flowers based on detailed textual input. The foundation of this project lies in leveraging deep learning algorithms, notably Generative Adversarial Networks (GANs) and recurrent neural networks, to achieve precise and high-quality image and video synthesis. The methodology involves extensive pre-training on diverse textual and visual datasets. Refining processes through user-generated data consistently improves the model’s performance and adaptability. The result will be a user-friendly and efficient application, empowering content creators, designers, and storytellers to effortlessly produce captivating visual content by providing descriptive text, thereby revolutionising the creation and sharing of multimedia content.