  At practical streaming bitrates, traditional video compression pipelines
frequently lead to visible artifacts that degrade perceptual quality. This
submission couples the effectiveness of a neural post-processor with a
different dynamic optimsation strategy for achieving an improved
bitrate/quality compromise. The neural post-processor is refined via
adversarial training and employs perceptual loss functions. By optimising the
post-processor and encoder directly our method demonstrates significant
improvement in video fidelity. The neural post-processor achieves substantial
VMAF score increases of +6.72 and +1.81 at bitrates of 50 kb/s and 500 kb/s
respectively.
