The authors explain an advance in synthetic image construction from still views. We enjoy the pleasant patter and the pretty pictures. post 
YOUTUBE zBSH-k9GbV4 Published Mar 1, 2022.
Though neural radiance fields (NeRF) have demonstrated impressive view synthesis results on objects and small bounded regions of space, they struggle on "unbounded" scenes, where the camera may point in any direction and content may exist at any distance.
Our model, which we dub "mip-NeRF 360" as we target scenes in which the camera rotates 360 degrees around a point, reduces mean-squared error by 54% compared to mip-NeRF, and is able to produce realistic synthesized views and detailed depth maps for highly intricate, unbounded real-world scenes.
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In this article, we will start with an explanation of what is Computer Graphics with a brief on volume rendering and view synthesis. We will then have an overview of what is Neural Radiance Fields and how it is used in view synthesis. medium