  The majority of internet traffic is video content. This drives the demand for
video compression to deliver high quality video at low target bitrates.
Optimising the parameters of a video codec for a specific video clip (per-clip
optimisation) has been shown to yield significant bitrate savings. In previous
work we have shown that per-clip optimisation of the Lagrangian multiplier
leads to up to 24% BD-Rate improvement. A key component of these algorithms is
modeling the R-D characteristic across the appropriate bitrate range. This is
computationally heavy as it usually involves repeated video encodes of the high
resolution material at different parameter settings. This work focuses on
reducing this computational load by deploying a NN operating on lower bandwidth
features. Our system achieves BD-Rate improvement in approximately 90% of a
large corpus with comparable results to previous work in direct optimisation.
