Saliency Detection via Manifold Ranking Based on Robust Foreground (original) (raw)

References

  1. S. Goferman, L. Zelnik-Manor, A. Tal. Context-aware saliency detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 10, pp. 1915–1926, 2012. DOI: https://doi.org/10.1109/TPAMI.2011.272.
    Article Google Scholar
  2. C. X. Guo, Z. B. Li, X. Qiao, C. Li, J. Yue. Image segmentation of underwater sea cucumber using GrabCut with saliency map. Transactions of the Chinese Society for Agricultural Machinery, vol. 46, no. S1, pp. 147–152, 2015. (in Chinese)
    Google Scholar
  3. X. F. Wang, C. Qi. An action recognition method using saliency detection. Journal of Xi’an Jiaotong University, vol. 52, no. 2, pp. 24–29, 44, 2018. DOI: https://doi.org/10.7652/xjtuxb201802004. (in Chinese)
    Google Scholar
  4. P. F. Yue, H. Y. Wang, Y. J. Zheng, Y. H. Zhao, J. Cui. Image retargeting using blur based depth saliency descriptor. Journal of Computer-Aided Design & Computer Graphics, vol. 30, no. 3, pp. 415–423, 2018. DOI: https://doi.org/10.3724/SP.J.1089.2018.16405. (in Chinese)
    Article Google Scholar
  5. J. Sun, P. Wang, Y. K. Luo, G. M. Hao, H. Qiao. Precision work-piece detection and measurement combining top-down and bottom-up saliency. International Journal of Automation and Computing, vol. 15, no. 4, pp. 417–430, 2018. DOI: https://doi.org/10.1007/s11633-018-1123-1.
    Article Google Scholar
  6. J. M. Yang, M. H. Yang. Top-down visual saliency via joint CRF and dictionary learning. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Providence, USA, pp. 2296–2303, 2012. DOI: https://doi.org/10.1109/CVPR.2012.6247940.
    Google Scholar
  7. N. Tong, H. C. Lu, X. Ruan, M. H. Yang. Salient object detection via bootstrap learning. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Boston, USA, pp. 1884–1892, 2015. DOI: https://doi.org/10.1109/CVPR.2015.7298798.
    Google Scholar
  8. H. Y. Li, H. C. Lu, Z. Lin, X. H. Shen, B. Price. Inner and inter label propagation: Salient object detection in the wild. IEEE Transactions on Image Processing, vol. 24, no. 10, pp. 3176–3186, 2015. DOI: https://doi.org/10.1109/TIP.2015.2440174.
    Article MathSciNet Google Scholar
  9. J. Y. Lü, Z. M. Tang. An improved graph-based manifold ranking for salient object detection. Journal of Electronics & Information Technology, vol. 37, no. 11, pp. 2555–2563, 2015. DOI: https://doi.org/10.11999/JEIT150619. (in Chinese)
    Google Scholar
  10. X. Lin, Y. L. Wang, H. L. Zhu, L. Z. Ma, L. H. Jiang. Saliency detection based on the Bayesian model of improved convex hull. Journal of Computer-Aided Design & Computer Graphics, vol. 29, no. 2, pp. 221–228, 2017. DOI: https://doi.org/10.3969/j.issn.1003-9775.2017.02.002. (in Chinese)
    Google Scholar
  11. D. M. Liu, F. L. Chang. Coarse-to-fine saliency detection based on non-subsampled contourlet transform enhancement. Acta Optica Sinica, vol. 39, no. 1, Article number 0115003, 2019. DOI: https://doi.org/10.3788/AOS201939.0115003. (in Chinese)
  12. M. M. Cheng, N. J. Mitra, X. L. Huang, P. H. S. Torr, S. M. Hu. Global contrast based salient region detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 3, pp. 569–582, 2015. DOI: https://doi.org/10.1109/TPAMI.2014.2345401.
    Article Google Scholar
  13. M. M. Cheng, G. X. Zhang, N. J. Mitra, X. L. Huang, S. M. Hu. Global contrast based salient region detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Providence, USA, pp. 409–416, 2011. DOI: https://doi.org/10.1109/CVPR.2011.5995344.
    Google Scholar
  14. T. Liu, Z. J. Yuan, J. Sun, J. D. Wang, N. N. Zheng, X. O. Tang, H. Y. Shum. Learning to detect a salient object. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 2, pp. 353–367, 2011. DOI: https://doi.org/10.1109/TPAMI.2010.70.
    Article Google Scholar
  15. Y. C. Wei, F. Wen, W. J. Zhu, J. Sun. Geodesic saliency using background priors. In Proceedings of the 12th European Conference on Computer Vision, Springer, Florence, Italy, pp. 29–42, 2012. DOI: https://doi.org/10.1007/978-3-642-33712-3_3.
  16. W. J. Zhu, S. Liang, Y. C. Wei, J. Sun. Saliency optimization from robust background detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Columbus, USA, pp. 2814–2821, 2014. DOI: https://doi.org/10.1109/CVPR.2014.360.
    Google Scholar
  17. C. Yang, L. H. Zhang, H. C. Lu, X. Ruan, M. H. Yang. Saliency detection via graph-based manifold ranking. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Portland, USA, pp. 3166–3173, 2013. DOI: https://doi.org/10.1109/CVPR.2013.407.
    Google Scholar
  18. Y. L. Xie, H. C. Lu. Visual saliency detection based on Bayesian model. In Proceedings of the 18th IEEE International Conference on Image Processing, IEEE, Brussels, Belgium, pp. 645–648, 2011. DOI: https://doi.org/10.1109/ICIP.2011.6116634.
    Google Scholar
  19. R. S. Liu, J. J. Cao, Z. C. Lin, S. G. Shan. Adaptive partial differential equation learning for visual saliency detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Columbus, USA, pp. 3866–3873, 2014. DOI: https://doi.org/10.1109/CVPR.2014.494.
    Google Scholar
  20. C. Wang, Y. Y. Fan, B. Li. Saliency detection based on robust foreground selection. Journal of Electronics & Information Technology, vol. 39, no. 11, pp. 2644–2651, 2017. DOI: https://doi.org/10.11999/JEIT170390. (in Chinese)
    Google Scholar
  21. H. H. Yeh, C. S. Chen. From rareness to compactness: Contrast-aware image saliency detection. In Proceedings of the 19th IEEE International Conference on Image Processing, IEEE, Orlando, USA, pp. 1077–1080, 2012. DOI: https://doi.org/10.1109/ICIP.2012.6467050.
    Google Scholar
  22. Q. Yan, L. Xu, J. P. Shi, J. Y. Jia. Hierarchical saliency detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Portland, USA, pp. 1155–1162, 2013. DOI: https://doi.org/10.1109/CVPR.2013.153.
    Google Scholar
  23. Z. J. Yao, T. Z. Tan. Saliency detection combining background and foreground prior. Journal of Image and Graphics, vol. 22, no. 10, pp. 1381–1391, 2017. DOI: https://doi.org/10.11834/jig.170114. (in Chinese)
    Google Scholar
  24. Z. L. Wang, G. H. Tian. Integrating manifold ranking with boundary expansion and corners clustering for saliency detection of home scene. Neurocomputing, vol. 379, pp. 182–196, 2020. DOI: https://doi.org/10.1016/j.neucom.2019.10.063.
    Article Google Scholar
  25. X. Lin, Z. X. Liu, X. M. Zheng, J. F. Huang, L. Z. Ma. Saliency detection based on improved manifold ranking via convex hull. Journal of Computer-Aided Design & Computer Graphics, vol. 31, no. 5, pp. 761–770, 2019. DOI: https://doi.org/10.3724/SP.J.1089.2019.17376. (in Chinese)
    Article Google Scholar
  26. Y. L. Xie, H. C. Lu, M. S. Yang. Bayesian saliency via low and mid level cues. IEEE Transactions on Image Processing, vol. 22, no. 5, pp. 1689–1698, 2013. DOI: https://doi.org/10.1109/TIP.2012.2216276.
    Article MathSciNet Google Scholar
  27. H. L. Zhu, B. Sheng, X. Lin, Y. Y. Hao, L. Z. Ma. Foreground object sensing for saliency detection. In Proceedings of ACM on International Conference on Multimedia Retrieval, ACM, New York, USA, pp. 111–118, 2016. DOI: https://doi.org/10.1145/2911996.2912008.
    Google Scholar
  28. R. Achanta, S. Hemami, F. Estrada, S. Susstrunk. Frequency-tuned salient region detection. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, IEEE, Miami, USA, pp. 1597–1604, 2009. DOI: https://doi.org/10.1109/CVPR.2009.5206596.
    Google Scholar

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