The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
How to Evaluate Foreground Maps
Abstract
The output of many algorithms in computer-vision is either non-binary maps or binary maps (e.g., salient object detection and object segmentation). Several measures have been suggested to evaluate the accuracy of these foreground maps. In this paper, we show that the most commonly-used measures for evaluating both non-binary maps and binary maps do not always provide a reliable evaluation. This includes the Area-Under-the-Curve measure, the Average-Precision measure, the F-measure, and the evaluation measure of the PASCAL VOC segmentation challenge. We start by identifying three causes of inaccurate evaluation. We then propose a new measure that amends these flaws. An appealing property of our measure is being an intuitive generalization of the F-measure. Finally we propose four meta-measures to compare the adequacy of evaluation measures. We show via experiments that our novel measure is preferable.
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Cites
The pascal visual object classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599
Contour Detection and Hierarchical Image Segmentation
Arbeláez, P., Maire, M., Fowlkes, C., & Malik, J. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.161 · Cited by 5,454
Frequency-tuned salient region detection
Achanta, R., Hemami, S., Estrada, F., & Susstrunk, S. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206596 · Cited by 4,167
Global contrast based salient region detection
Cheng, M.-M., Zhang, G.-X., Mitra, N. J., Huang, X., & Hu, S.-M. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995344 · Cited by 2,976
Saliency filters: Contrast based filtering for salient region detection
Perazzi, F., Krahenbuhl, P., Pritch, Y., & Hornung, A. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247743 · Cited by 2,110
Learning to Detect a Salient Object
Liu, T., Yuan, Z., Sun, J., Wang, J., Zheng, N., Tang, X., & Shum, H.-Y. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.70 · Cited by 1,777
Content-based multimedia information retrieval: State of the art and challenges
Lew, M. S., Sebe, N., Djeraba, C., & Jain, R. (2006) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/1126004.1126005 · Cited by 1,528
Geodesic Saliency Using Background Priors
Wei, Y., Wen, F., Zhu, W., & Sun, J. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33712-3_3 · Cited by 842
Context-aware saliency detection
Goferman, S., Zelnik-Manor, L., & Tal, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539929 · Cited by 753
Self-citationA unified approach to salient object detection via low rank matrix recovery
Shen, X., & Wu, Y. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247758 · Cited by 691
Cited by
Structure-Measure: A New Way to Evaluate Foreground Maps
Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., & Borji, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.487 · Cited by 2,092
Enhanced-alignment Measure for Binary Foreground Map Evaluation
Fan, D.-P., Gong, C., Cao, Y., Ren, B., Cheng, M.-M., & Borji, A. (2018) · Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/97 · Cited by 1,607
Salient Object Detection: A Benchmark
Borji, A., Cheng, M.-M., Jiang, H., & Li, J. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2487833 · Cited by 1,364
What Do Different Evaluation Metrics Tell Us About Saliency Models?
Bylinskii, Z., Judd, T., Oliva, A., Torralba, A., & Durand, F. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2815601 · Cited by 802
Camouflaged Object Segmentation with Distraction Mining
Mei, H., Ji, G.-P., Wei, Z., Yang, X., Wei, X., & Fan, D.-P. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00866 · Cited by 565
Metadata
- Authors
- Margolin, R., Zelnik-Manor, L., & Tal, A.
- Venue
- 2014 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2014-06
- Pages
- 248-255
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1994922096
- Cited by
- 1,106
- References
- 24
- FWCI
- 12.61
- Type
- conference paper
- Language
- en
- Open access
- closed
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