Text Driven Image Manipulation

Text-driven image manipulation uses natural language descriptions to modify images, aiming to create flexible and user-friendly image editing tools. Current research focuses on improving the accuracy and efficiency of these manipulations, often employing diffusion models, transformer networks, and vision-language models like CLIP, with a strong emphasis on disentangling editing effects and achieving real-time performance. This field is significant for its potential to revolutionize image editing workflows across various applications, from creative design to medical imaging, by offering intuitive and powerful control over image content and style.