research-article

Image completion using planar structure guidance

Authors:

Sing Bing Kang,

Narendra Ahuja,

Johannes KopfAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 33, Issue 4

Article No.: 129, Pages 1 - 10

https://doi.org/10.1145/2601097.2601205

Published: 27 July 2014 Publication History

Abstract

We propose a method for automatically guiding patch-based image completion using mid-level structural cues. Our method first estimates planar projection parameters, softly segments the known region into planes, and discovers translational regularity within these planes. This information is then converted into soft constraints for the low-level completion algorithm by defining prior probabilities for patch offsets and transformations. Our method handles multiple planes, and in the absence of any detected planes falls back to a baseline fronto-parallel image completion algorithm. We validate our technique through extensive comparisons with state-of-the-art algorithms on a variety of scenes.

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Cited By

Wei LTianqiang HLiqing HAokun ZChao X(2024)Large-scale datasets for facial tampering detection with inpainting techniquesJournal of Image and Graphics10.11834/jig.23042229:7(1834-1848)Online publication date: 2024
https://doi.org/10.11834/jig.230422
Yu HYang RYu J(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
https://doi.org/10.1117/1.JEI.33.1.013036
Shang QHu HYu HXu BWang LZhu Q(2024)Semantic Image Translation for Repairing the Texture Defects of Building ModelsIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2023.333896262(1-20)Online publication date: 2024
https://doi.org/10.1109/TGRS.2023.3338962
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Index Terms

Image completion using planar structure guidance
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Graphics recognition and interpretation
2. Computing methodologies
  1. Computer graphics

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 33, Issue 4

July 2014

1366 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2601097

Issue’s Table of Contents

Copyright © 2014 ACM.

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 the author(s) 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 July 2014

Published in TOG Volume 33, Issue 4

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Cited By

Wei LTianqiang HLiqing HAokun ZChao X(2024)Large-scale datasets for facial tampering detection with inpainting techniquesJournal of Image and Graphics10.11834/jig.23042229:7(1834-1848)Online publication date: 2024
https://doi.org/10.11834/jig.230422
Yu HYang RYu J(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
https://doi.org/10.1117/1.JEI.33.1.013036
Shang QHu HYu HXu BWang LZhu Q(2024)Semantic Image Translation for Repairing the Texture Defects of Building ModelsIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2023.333896262(1-20)Online publication date: 2024
https://doi.org/10.1109/TGRS.2023.3338962
Li YHu LDong LWu HTian JZhou JLi X(2024)Transformer-Based Image Inpainting Detection via Label Decoupling and Constrained Adversarial TrainingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.329927834:3(1857-1872)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1109/TCSVT.2023.3299278
Park JHong CBaik SLee K(2024)CoLaNet: Adaptive Context and Latent Information Blending for Face Image InpaintingIEEE Signal Processing Letters10.1109/LSP.2023.334099831(91-95)Online publication date: 2024
https://doi.org/10.1109/LSP.2023.3340998
Li CZhang ZLi PHe Z(2024)I3FDM: IRIS Inpainting Via Inverse Fusion of Diffusion ModelsICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10447757(1636-1640)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSP48485.2024.10447757
Kim TKim JOh HKang J(2024)Deep Transformer Based Video Inpainting Using Fast Fourier TokenizationIEEE Access10.1109/ACCESS.2024.336128312(21723-21736)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3361283
Srinivasan MChinnadurai MSenthilkumar SDinesh E(2024)An effective video inpainting technique using morphological Haar wavelet transform with krill herd based criminisi algorithmScientific Reports10.1038/s41598-024-66496-x14:1Online publication date: 5-Jul-2024
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Chen WZhang DMa JWu G(2024)A comprehensive system for 3D display: From image capture to autostereoscopic playbackDisplays10.1016/j.displa.2023.10257281(102572)Online publication date: Jan-2024
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Quan WChen JLiu YYan DWonka P(2024)Deep Learning-Based Image and Video Inpainting: A SurveyInternational Journal of Computer Vision10.1007/s11263-023-01977-6132:7(2367-2400)Online publication date: 1-Jul-2024
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