  This paper presents improvements and novel additions to our recent work on
end-to-end optimized hierarchical bi-directional video compression to further
advance the state-of-the-art in learned video compression. As an improvement,
we combine motion estimation and prediction modules and compress refined
residual motion vectors for improved rate-distortion performance. As novel
addition, we adapted the gain unit proposed for image compression to
flexible-rate video compression in two ways: first, the gain unit enables a
single encoder model to operate at multiple rate-distortion operating points;
second, we exploit the gain unit to control bit allocation among intra-coded
vs. bi-directionally coded frames by fine tuning corresponding models for truly
flexible-rate learned video coding. Experimental results demonstrate that we
obtain state-of-the-art rate-distortion performance exceeding those of all
prior art in learned video coding.
