Low Level Vision Task

Low-level vision tasks focus on fundamental image processing operations like denoising, super-resolution, and image fusion, aiming to improve image quality and extract basic visual features. Current research emphasizes developing efficient and generalizable models, including transformers and diffusion models, often incorporating techniques like weight modulation and task-specific prompts to handle multiple tasks simultaneously or improve model interpretability through causal analysis. These advancements are crucial for improving the performance and reliability of various applications, from mobile device image processing to enhancing the capabilities of larger multimodal AI systems.