  There has been a growing interest in using different approaches to improve
the coding efficiency of modern video codec in recent years as demand for
web-based video consumption increases. In this paper, we propose a model-based
approach that uses texture analysis/synthesis to reconstruct blocks in texture
regions of a video to achieve potential coding gains using the AV1 codec
developed by the Alliance for Open Media (AOM). The proposed method uses
convolutional neural networks to extract texture regions in a frame, which are
then reconstructed using a global motion model. Our preliminary results show an
increase in coding efficiency while maintaining satisfactory visual quality.
