The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Evaluation of GIST descriptors for web-scale image search
Open accessAbstract
International audience
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Lazebnik, S., Schmid, C., & Ponce, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.68 · Cited by 7,916
Self-citationVideo Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
Scale & Affine Invariant Interest Point Detectors
Mikolajczyk, K., & Schmid, C. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000027790.02288.f2 · Cited by 3,436
Self-citationHamming Embedding and Weak Geometric Consistency for Large Scale Image Search
Jegou, H., Douze, M., & Schmid, C. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88682-2_24 · Cited by 1,901 · cited 10×
“It is derived from [5], which employs an inverted file [25].”
BackgroundMethodResultInfluentialSelf-citationRobust Wide Baseline Stereo from Maximally Stable Extremal Regions
Matas, J., Chum, O., Urban, M., & Pajdla, T. (2002) · Procedings of the British Machine Vision Conference 2002 · doi:10.5244/c.16.36 · Cited by 1,350
Small codes and large image databases for recognition
Torralba, A., Fergus, R., & Weiss, Y. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587633 · Cited by 727
Research works printed but not linked: 19
- 10.1109/ICCV.2007.4408891 · DOI · Paper page
- 10.5244/C.22.50 · DOI · Paper page
- M. Douze , A. Gaidon , H. Jégou , M. Marszalek , and C. Schmid . INRIA-LEAR's video copy detection system . In TRECVID Workshop , November 2008 . M. Douze, A. Gaidon, H. Jégou, M. Marszalek, and C. Schmid. INRIA-LEAR's video copy detection system. In TRECVID Workshop, November 2008.
- 10.1145/1275808.1276382 · DOI · Paper page
- H. Jégou , M. Douze , and C. Schmid . Hamming embedding and weak geometry consistency for large scale image search - extended version. Technical report , INRIA, RR 6709, October 2008 . H. Jégou, M. Douze, and C. Schmid. Hamming embedding and weak geometry consistency for large scale image search - extended version. Technical report, INRIA, RR 6709, October 2008.
- 10.1109/CVPR.2007.382970 · DOI
- 10.1145/1180639.1180760 · DOI
- 10.1007/978-3-540-88682-2_33 · DOI · Paper page
- K. Mikolajczyk . Binaries for affine covariant region descriptors , 2007 . K. Mikolajczyk. Binaries for affine covariant region descriptors, 2007.
- 10.1109/CVPR.2006.264 · DOI · Paper page
- 10.1023/A:1011139631724 · DOI · Paper page
- 10.1109/CVPR.2007.383172 · DOI · Paper page
- 10.1109/CVPR.2008.4587635 · DOI · Paper page
- 10.1016/0306-4573(88)90021-0 · DOI · Paper page
- 10.5555/946247.946751 · doi:10.5555/946247.946751
- 10.1145/1178677.1178722 · DOI · Paper page
- 10.1109/TPAMI.2008.128 · DOI · Paper page
- Y. Weiss , A. Torralba , and R. Fergus . Spectral hashing . In Advances in Neural Information Processing Systems , 2009 . Y. Weiss, A. Torralba, and R. Fergus. Spectral hashing. In Advances in Neural Information Processing Systems, 2009.
- 10.1145/296854.277632 · DOI · Paper page
Cited by
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684
Emerging Properties in Self-Supervised Vision Transformers
Caron, M., Touvron, H., Misra, I., Jegou, H., Mairal, J., Bojanowski, P., & Joulin, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00951 · Cited by 5,638
“We report the mAP performance in copy detection on Copydays “strong” subset [21].”
MethodSelf-citationProduct Quantization for Nearest Neighbor Search
Jégou, H., Douze, M., & Schmid, C. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.57 · Cited by 2,956
“When no supervision is used, this mapping is learned such that the neighborhood in the embedded space defined by the Hamming distance reflects the neighborhood in the Euclidean space of the original features.”
MethodSelf-citationRegion-based convolutional networks for accurate object detection and segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2437384 · Cited by 2,912
Metadata
- Authors
- Douze, M., Jégou, H., Sandhawalia, H., Amsaleg, L., & Schmid, C.
- Venue
- Proceedings of the ACM International Conference on Image and Video Retrieval
- Publisher
- ACM
- Published
- 2009-07-08
- Pages
- 1-8
- OpenAlex
- W2020308406
- Cited by
- 394
- References
- 7
- FWCI
- 20.17
- Type
- conference paper
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Evaluation of GIST descriptors for web-scale image search. https://app.cochat.ai/papers/10.1145/1646396.1646421
- The paper
- Douze, M., Jégou, H., Sandhawalia, H., Amsaleg, L., & Schmid, C. (2009). Evaluation of GIST descriptors for web-scale image search. Proceedings of the ACM International Conference on Image and Video Retrieval. https://doi.org/10.1145/1646396.1646421
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.