Learning to Compress Videos without Computing Motion

29 Sep 2020 Meixu Chen Todd Goodall Anjul Patney Alan C. Bovik

With the development of higher resolution contents and displays, its significant volume poses significant challenges to the goals of acquiring, transmitting, compressing and displaying high quality video content. In this paper, we propose a new deep learning video compression architecture that does not require motion estimation, which is the most expensive element of modern hybrid video compression codecs like H.264 and HEVC... (read more)

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