Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Single-View View Synthesis with Multiplane Images   A recent strand of work in view synthesis uses deep learning to generate
multiplane images (a camera-centric, layered 3D representation) given two or
more input images at known viewpoints. We apply this representation to
single-view view synthesis, a problem which is more challenging but has
potentially much wider application. Our method learns to predict a multiplane
image directly from a single image input, and we introduce scale-invariant view
synthesis for supervision, enabling us to train on online video. We show this
approach is applicable to several different datasets, that it additionally
generates reasonable depth maps, and that it learns to fill in content behind
the edges of foreground objects in background layers.
  Project page at https://single-view-mpi.github.io/.

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The categories of this paper are: eess
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The categories of this paper are: physics
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The categories of this paper are: patt-sol
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The categories of this paper are: econ
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The categories of this paper are: ao-sci
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-ex
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The categories of this paper are: math-ph
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The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: comp-gas
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The categories of this paper are: alg-geom
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The categories of this paper are: supr-con
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The categories of this paper are: q-bio
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The categories of this paper are: hep-th
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The categories of this paper are: astro-ph