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KIAM Preprint № 81, Moscow, 2020
Authors: Frolov V.A., Feklisov E.D., Trofimiv M.A., Voloboy A.G.
Synthesis of images of interiors for training neural networks
Abstract:
The paper proposes a number of methods that can be used to synthesize images of interiors in order to train artificial intelligence. The proposed methods solve the problem of generating training samples in a complex, starting from automatic generation of 3D content and ending with rendering directly. One of the main goals of the develioed system is to provide sufficient performance when generating sets of photo-realistic images of interiors via using GPUs.
Keywords:
Synthesis of images of interiors for training neural networks, interior sampling
Publication language: russian,  pages: 20
Research direction:
Programming, parallel computing, multimedia
Russian source text:
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About authors:
  • Frolov Vladimir Alexandrovich,  vfrolov@graphics.cs.msu.ruorcid.org/0000-0001-8829-9884KIAM RAS
  • Feklisov Egor Dmitrievich,  egor.feklisov@graphics.cs.msu.ruorcid.org/0000-0003-0593-4251,  Lomonosov Moscow State University
  • Trofimiv Maxim Alexandrovich,  trofimovmax@mail.ruorcid.org/0000-0001-6098-6121,  Lomonosov Moscow State University
  • Voloboy Alexey Gennadievich,  voloboy@gin.keldysh.ruorcid.org/0000-0003-1252-8294KIAM RAS