Cited by 22Advanced Image and Video Retrieval TechniquesSatellite Image Processing and PhotogrammetryImage Retrieval and Classification Techniques

Triple Robustness Augmentation Local Features for multi-source image registration

Wang, Changwei, Xu, Lele, Xu, Rongtao, Xu, Shibiao, Meng, Weiliang, Wang, Ruisheng, Zhang, Xiaopeng·2023·ISPRS Journal of Photogrammetry and Remote Sensing

Integrity signals

Registry

Crossref · 10.1016/j.isprsjprs.2023.03.023

Cites

76 of 76 references verified0 citation errors · 0 not checkable

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  • Integrating learned depth and optical flow predictions yields consistent pose estimations and improves monocular system accuracy.

    “By integrating learned depth and optical flow predictions [134], these systems achieve consistent pose estimations, improving monocular system accuracy.”

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Authors
Wang, C., Xu, L., Xu, R., Xu, S., Meng, W., Wang, R., & Zhang, X.
Affiliations
  • University of Calgary (CA)
  • Beijing University of Posts and Telecommunications (CN)
  • Chinese Academy of Sciences (CN)
Corresponding author
  • Xu, Lele
  • Xu, Rongtao
  • Xu, Shibiao
Venue
ISPRS Journal of Photogrammetry and Remote Sensing
Publisher
Elsevier BV
Published
2023-05
Volume
199
Pages
1-14
ISSN
0924-2716 (ISSN-L)
OpenAlex
W4362449280
Cited by
22
References
76
Citations by year
2026: 5 · 2025: 10 · 2024: 6 · 2023: 1
FWCI
2.00
Type
journal article
Language
en
Open access
closed
Locations
ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
  • Physical Sciences › Engineering › Ocean Engineering › Satellite Image Processing and Photogrammetry
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
Keywords
local features, rotation robustness, scale robustness, cross-domain alignment, keypoint detection, remote sensing images

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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