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Computer Science > Computer Vision and Pattern Recognition

arXiv:2108.05892 (cs)
[Submitted on 12 Aug 2021]

Title:PixelSynth: Generating a 3D-Consistent Experience from a Single Image

Authors:Chris Rockwell, David F. Fouhey, Justin Johnson
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Abstract:Recent advancements in differentiable rendering and 3D reasoning have driven exciting results in novel view synthesis from a single image. Despite realistic results, methods are limited to relatively small view change. In order to synthesize immersive scenes, models must also be able to extrapolate. We present an approach that fuses 3D reasoning with autoregressive modeling to outpaint large view changes in a 3D-consistent manner, enabling scene synthesis. We demonstrate considerable improvement in single image large-angle view synthesis results compared to a variety of methods and possible variants across simulated and real datasets. In addition, we show increased 3D consistency compared to alternative accumulation methods. Project website: this https URL
Comments: In ICCV 2021
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2108.05892 [cs.CV]
  (or arXiv:2108.05892v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2108.05892

Submission history

From: Chris Rockwell [view email]
[v1] Thu, 12 Aug 2021 17:59:31 UTC (6,545 KB)
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