Low-complexity research for next-generation VVC standard and its neural network extension

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This research aims at reducing the complexity of the latest video compression standard Versatile Video Coding (VVC), from the aspect of both algorithm and architecture. For the algorithm, we developed a fast intra encoding for video coding for machine (VCM) framework, and a low complexity convolutional neural network filter. For the architecture, we proposed a reconfigurable multiple transform selection architecture for VVC.