Scale Upsampling

Scale upsampling aims to increase the resolution of data, such as images, videos, or point clouds, often improving quality and detail. Current research focuses on developing efficient and versatile upsampling methods, employing architectures like transformers, generative adversarial networks (GANs), and diffusion models, often incorporating multi-scale processing and adaptive strategies to handle varying upsampling ratios and input characteristics. These advancements are significant for diverse applications, including image processing, speech enhancement, video compression, and 3D computer vision, enabling higher-quality outputs and improved performance in various tasks.