Multi Task Image Restoration

Multi-task image restoration aims to develop single models capable of correcting various image degradations simultaneously, improving efficiency and reducing computational costs compared to single-task approaches. Current research focuses on designing architectures that effectively handle diverse task demands, often employing techniques like multi-expert selection, visual prompts, and the integration of vision-language models to guide the restoration process. These advancements are improving the quality and versatility of image restoration, with applications ranging from preserving cultural artifacts to enhancing e-commerce product images. The field is actively exploring methods to balance task performance and leverage shared information between different restoration tasks.