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Scene completion using millions of photographs

Published: 29 July 2007 Publication History

Abstract

What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images is effectively infinite, the space of semantically differentiable scenes is actually not that large. For many image completion tasks we are able to find similar scenes which contain image fragments that will convincingly complete the image. Our algorithm is entirely data-driven, requiring no annotations or labelling by the user. Unlike existing image completion methods, our algorithm can generate a diverse set of results for each input image and we allow users to select among them. We demonstrate the superiority of our algorithm over existing image completion approaches.

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Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 26, Issue 3
July 2007
976 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/1276377
Issue’s Table of Contents
  • cover image ACM Overlay Books
    Seminal Graphics Papers: Pushing the Boundaries, Volume 2
    August 2023
    893 pages
    ISBN:9798400708978
    DOI:10.1145/3596711
    • Editor:
    • Mary C. Whitton
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 29 July 2007
Published in TOG Volume 26, Issue 3

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Author Tags

  1. hole filling
  2. image completion
  3. image compositing
  4. image database
  5. inpainting

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  • (2024)Repairing the in situ hybridization missing data in the hippocampus region by using a 3D residual U-Net modelBiomedical Optics Express10.1364/BOE.52207815:6(3541)Online publication date: 1-May-2024
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  • (2024)Mutual encoder-decoder with bi-gated convolution for image inpaintingJournal of Electronic Imaging10.1117/1.JEI.33.1.01303633:01Online publication date: 1-Jan-2024
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