GAN

The intersection of artificial intelligence and multimedia continues to evolve, breaking down barriers between different forms of media. In this project, the research titled “Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators” conducted by Picsart AI Research Lab represents a significant breakthrough. This study introduces a pioneering method that directly converts textual descriptions into videos, bridging the gap between natural language processing and computer vision. This development not only caters to the growing demand for dynamic visual content but also showcases the machine’s capability to interpret and transform human language into a visual format. By addressing the challenge of text-to-video synthesis, this research sets a new standard for interdisciplinary studies in artificial intelligence. ...

Special thanks to Mega Satish and Hasan Rizvi for their meaningful contributions, support, and wisdom that helped shape this work. In the present study, we propose to implement a new framework for estimating generative models via an adversarial process to extend an existing GAN framework and develop a white-box controllable image cartoonization, which can generate high-quality cartooned images/videos from real-world photos and videos.