Detail Restoration

Detail restoration in image and video processing aims to recover lost or degraded information, improving image quality and enabling more accurate analysis. Current research emphasizes developing adaptable and generalizable models, often leveraging diffusion models and incorporating multimodal prompts (text and image) to guide the restoration process, achieving better fidelity and control over the outcome. This work is crucial for various applications, from medical imaging (e.g., removing motion artifacts in MRI) to enhancing the accuracy of object detection and recognition in computer vision, by ensuring the correct restoration of fine details.