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DTSTAMP:20240214T070243Z
LOCATION:Meeting Room C4.9+C4.10\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T170000
DTEND;TZID=Australia/Melbourne:20231212T171000
UID:siggraphasia_SIGGRAPH Asia 2023_sess162_papers_307@linklings.com
SUMMARY:SinMPI: Novel View Synthesis from a Single Image with Expanded Mul
 tiplane Images
DESCRIPTION:Technical Papers\n\nGuo Pu, Peng-Shuai Wang, and Zhouhui Lian 
 (Wangxuan Institute of Computer Technology, Peking University)\n\nSingle-i
 mage novel view synthesis is a challenging and ongoing problem that aims t
 o generate an infinite number of consistent views from a single input imag
 e. Although significant efforts have been made to advance the quality of g
 enerated novel views, less attention has been paid to the expansion of the
  underlying scene representation, which is crucial to the generation of re
 alistic novel view images. This paper proposes SinMPI, a novel method that
  uses expanded multiplane images (MPIs) as the 3D scene representation to 
 significantly expand the perspective range of MPIs and generate high-quali
 ty novel views from a large multiplane space. The key idea of our method i
 s to use Stable Diffusion~\cite{rombach2021highresolution} to generate out
 -of-view contents, project all scene contents into expanded multiplane ima
 ges, and then optimize the multiplane images under the supervision of pseu
 do-multi-view data generated by a depth-aware warping and inpainting modul
 e. Both qualitative and quantitative experiments have been conducted to va
 lidate the superiority of our method to the state of the art. Our code and
  data are available at https://github.com/TrickyGo/SinMPI.\n\nRegistration
  Category: Full Access\n\nSession Chair: Binh-Son Hua (Trinity College Dub
 lin)
URL:https://asia.siggraph.org/2023/full-program?id=papers_307&sess=sess162
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