The Application of Generative AI and Intelligent Agents in Low-level Vision

In this tutorial, we will introduce the recent progress of low-level image processing with Generative AI and Intelligent Agents, which aims to utilize the brand-new generative foundation models, e.g., diffusion models, large language models (LLMs) and multi-modal large language models (MLLMs) to tackle several pivotal challenges, e.g., perception quality, multi-modality information compensation, universality, automatic human-computer interaction (HCI) in the low-level image processing.

Specifically, we first briefly introduce the definition of generative AI and Intelligent Agents, followed by their categories and progress on the applications in various fields. Second, we shed light on the advances of low-level image processing with Generative AI, including diffusion models, large language models (LLMs) and multi-modal large language models (MLLMs). Third, we provide a systematic review for the advancement of intelligent Agents in low-level image processing for Image Compression, Image Restoration/Enhancement and Image Quality Assessment.

Last but not least, we will discuss the challenges and potential directions of low-level image processing with Generative AI- and Intelligent Agents from the perspectives: (i) universal framework; (ii) interactive paradigm; and (iii) multi-agent cooperation.