Learning-based Visual Compression

Visual compression is an application of data compression to lower the storage and/or transmission requirements for digital images and videos. Due to the rapid growth in visual data transmission demand, more efficient compression algorithms are needed. Considering that deep learning techniques have successfully revolutionized many visual tasks, learning-based compression algorithms have been explored over the years and have been shown to be able to outperform many conventional compression methods. This survey provides a review of various visual compression algorithms, both end-to-end learning-based image compression approaches and hybrid image compression approaches. Some learningbased video compression methods are also discussed. In addition to describing a wide range of learning-based image compression approaches that have been developed in recent years, the survey describes widely used datasets, presents recent standardization efforts, and discusses potential research directions.