Video Enhancement

Video enhancement aims to improve the quality of videos by addressing issues like noise, low light, blur, and low resolution. Current research focuses on leveraging deep learning, particularly diffusion models, generative adversarial networks (GANs), and recurrent memory transformers, often incorporating motion information and geometric priors for improved accuracy and efficiency. These advancements are driving progress in various applications, including medical imaging, surveillance, and film restoration, with a growing emphasis on developing robust and efficient methods suitable for real-time processing on mobile devices and accurate quality assessment metrics.