Deep Video Compression

Deep video compression leverages deep learning to achieve significantly higher compression ratios than traditional codecs, primarily by learning efficient representations of video data and exploiting temporal redundancy between frames. Current research focuses on improving the efficiency of bidirectional prediction, developing task-adaptive encoders, and addressing uncertainties in motion estimation through techniques like deep ensembles and refined optical flow processing. These advancements promise substantial improvements in video storage and transmission efficiency, impacting applications ranging from high-resolution video streaming to virtual reality.