Low Level Vision

Low-level vision focuses on fundamental image processing tasks like denoising, super-resolution, and inpainting, aiming to improve image quality and extract basic visual features. Current research emphasizes the application of deep generative models, particularly diffusion models and transformers, often within large language model (LLM) frameworks, to enhance performance and address challenges like hallucinations and the need for efficient computation. This field is crucial for advancing various applications, from medical image analysis and synthetic image detection to improving the reliability and capabilities of AI systems that rely on visual input. Benchmarking efforts are underway to standardize evaluation and drive further progress in this important area.