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The task of synthesizing novel views from a single image has usefulapplications in virtual reality and mobile computing, and a number ofapproaches to the problem have been proposed in recent years. A MultiplaneImage (MPI) estimates the scene as a stack of RGBA layers, and can modelcomplex appearance effects, anti-alias depth errors and synthesize soft edgesbetter than methods that use textured meshes or layered depth images. Andunlike neural radiance fields, an MPI can be efficiently rendered on graphicshardware. However, MPIs are highly redundant and require a large number ofdepth layers to achieve plausible results. Based on the observation that thedepth complexity in local image regions is lower than that over the entireimage, we split an MPI into many small, tiled regions, each with only a fewdepth planes. We call this representation a Tiled Multiplane Image (TMPI). Wepropose a method for generating a TMPI with adaptive depth planes forsingle-view 3D photography in the wild. Our synthesized results are comparableto state-of-the-art single-view MPI methods while having lower computationaloverhead.

Tiled Multiplane Images for Practical 3D Photography