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Image Classification with the Fisher Vector: Theory and Practice
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“Compared with the conventional methods, FV is able to obtain high discriminative subspace with the complementary feature subspace exploration.”
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“It is known that the widely used SIFT23 achieves superior performance compared to other descriptors such as color especially in the computer vision field.”
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Metadata
- Authors
- Sánchez, J., Perronnin, F., Mensink, T., & Verbeek, J.
- Affiliations
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Xerox (France) (FR)
- University of Amsterdam (NL)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Corresponding author
- Sánchez, Jorge
- Venue
- International Journal of Computer Vision
- Published
- 2013-06-12
- Volume
- 105
- Issue
- 3
- Pages
- 222-245
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1966385142
- Cited by
- 1,498
- References
- 85
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 45 · 2023: 58 · 2022: 102 · 2021: 95 · 2020: 128 · 2019: 164 · 2018: 167 · 2017: 211 · 2016: 224 · 2015: 167 · 2014: 91 · 2013: 13
- FWCI
- 171.88
- Type
- journal article
- Language
- en
- Open access
- green
- handle.uba.uva.nl
- Licence
- www.springer.com/tdm (tdm)
- Locations
- International Journal of Computer Vision (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- HAL (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- Fisher vectors, Fisher kernel, image classification, bag of visual words, product quantization, image retrieval, feature encoding, linear classifiers
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 ›
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