Real-Time Implementation of Neural-Network Post-Filters for 4K 60fps VVC Videos

This study investigates the practical performance of neural-network post-filters standardized in ITU-T H.274. We implement neural-network models on a Field-Programmable Gate Array (FPGA), allowing real-time processing of 4K 60fps encoded videos transmitted via 12G-SDI. Experimental results suggest that a minor bitrate increase for the transmission of the neural-network model weights can enhance the quality of the videos encoded by Versatile Video Coding (VVC).