Enhancement Network

Enhancement networks are deep learning models designed to improve the quality of various data types, including images, videos, and audio signals, by addressing issues like low light, blur, noise, and missing modalities. Current research focuses on developing efficient architectures, such as encoder-decoder structures and transformers, often incorporating techniques like wavelet transforms, latent disentanglement, and multi-scale feature processing to enhance specific aspects of the data. These advancements have significant implications for diverse fields, improving the performance of applications ranging from autonomous driving and medical imaging to speech recognition and non-line-of-sight imaging.