Analysis of Neural Video Compression Networks for 360-Degree Video Coding
arxiv(2024)
摘要
With the increasing efforts of bringing high-quality virtual reality
technologies into the market, efficient 360-degree video compression gains in
importance. As such, the state-of-the-art H.266/VVC video coding standard
integrates dedicated tools for 360-degree video, and considerable efforts have
been put into designing 360-degree projection formats with improved compression
efficiency. For the fast-evolving field of neural video compression networks
(NVCs), the effects of different 360-degree projection formats on the overall
compression performance have not yet been investigated. It is thus unclear,
whether a resampling from the conventional equirectangular projection (ERP) to
other projection formats yields similar gains for NVCs as for hybrid video
codecs, and which formats perform best. In this paper, we analyze several
generations of NVCs and an extensive set of 360-degree projection formats with
respect to their compression performance for 360-degree video. Based on our
analysis, we find that projection format resampling yields significant
improvements in compression performance also for NVCs. The adjusted cubemap
projection (ACP) and equatorial cylindrical projection (ECP) show to perform
best and achieve rate savings of more than 55
for the most recent NVC. Remarkably, the observed rate savings are higher than
for H.266/VVC, emphasizing the importance of projection format resampling for
NVCs.
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