Image Artifact

Image artifacts, unwanted distortions or imperfections in images, are a significant challenge across diverse applications, from online shopping to medical imaging. Current research focuses on developing methods to detect and remove these artifacts, employing techniques like generative adversarial networks, image-to-image translation models, and invertible neural networks tailored to specific artifact types (e.g., scratches, noise, AI-generated anomalies). These advancements aim to improve image quality, enhance the reliability of AI-generated content, and enable more accurate analysis in fields such as medical imaging and product visualization.

Papers