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
December 28, 2024
December 22, 2024
August 12, 2024
September 12, 2023
February 11, 2023
April 24, 2022
February 26, 2022