"New AI Techniques for Image Compression and Visual Question Answering"

Google researchers proposed a method that combines a standard autoencoder with a diffusion process to efficiently compress high-quality images using score-based generative models. The proposed method outperforms several recent generative approaches in terms of image quality and preserves details much better compared to state-of-the-art approaches. The study revealed specific details that can be useful for future research in this domain, such as the impact of noise schedule and the amount of noise injected during image generation.