The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Computer Vision – ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part VI
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The Variational Bayes method estimates mean posteriori values.
“The first method based on the probabilistic Bayes model is the Variational Bayes method [21, 22], which estimates the mean posteriori values.”
From A Comprehensive Review of Blind Deconvolution Techniques for Image Deblurring (2020) · cites this paper as [21]
The Variational Bayes method is effective in accurate PSF estimation for various types of blurs such as motion blur and out-of-focus blur in various images.
“This method is effective in accurate PSF estimation for various types of blurs such as motion blur, out-of-focus blur in various images”
From A Comprehensive Review of Blind Deconvolution Techniques for Image Deblurring (2020) · cites this paper as [21]
Citations
Cites
A Naturalistic Open Source Movie for Optical Flow Evaluation
Butler, D. J., Wulff, J., Stanley, G. B., & Black, M. J. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33783-3_44 · Cited by 1,842
Flagged first, then by citations
Cited by
Sorted by citations
A Comprehensive Review of Blind Deconvolution Techniques for Image Deblurring
Satish, P., Srikantaswamy, M., & Ramaswamy, N. (2020) · Traitement du signal · doi:10.18280/ts.370321 · Cited by 59
Metadata
- Authors
- Fitzgibbon, A., Schmid, C., Sato, Y., Perona, P., & Lazebnik, S.
- Affiliations
- Microsoft Research (United Kingdom) (GB)
- University of North Carolina at Chapel Hill (US)
- California Institute of Technology (US)
- Institute of Industrial Science, The University of Tokyo (JP)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4241103812
- Cited by
- 38
- References
- 1
- Citations by year
- 2025: 1 · 2024: 9 · 2023: 3 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 8 · 2018: 3 · 2017: 1 · 2016: 1 · 2015: 3 · 2014: 3
- FWCI
- 1.36
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- DIAL (Catholic University of Leuven) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Keywords
- computer vision
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
