Shot Personalization

Shot personalization aims to tailor generative models, such as text-to-image and language models, to individual users using minimal data, typically a single image or a few examples. Current research focuses on efficient fine-tuning strategies for pre-trained models, often employing techniques like selective parameter updates, Gaussian priors for 3D modeling, and adapter modules for style transfer. This area is significant because it enables personalized experiences in various applications, from creating customized avatars and stylized images to generating personalized text responses, while addressing the limitations of data scarcity and computational cost.