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Depth saliency based on anisotropic center-surround difference
Abstract
Most previous works on saliency detection are dedicated to 2D images. Recently it has been shown that 3D visual information supplies a powerful cue for saliency analysis. In this paper, we propose a novel saliency method that works on depth images based on anisotropic center-surround difference. Instead of depending on absolute depth, we measure the saliency of a point by how much it outstands from surroundings, which takes the global depth structure into consideration. Besides, two common priors based on depth and location are used for refinement. The proposed method works within a complexity of O(N) and the evaluation on a dataset of over 1000 stereo images shows that our method outperforms state-of-the-art.
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Cited by
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders
Zhang, J., Fan, D.-P., Dai, Y., Anwar, S., Saleh, F. S., Zhang, T., & Barnes, N. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00861 · Cited by 423
Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection
Chen, H., & Li, Y. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00322 · Cited by 336
RGB-D salient object detection: A survey
Zhou, T., Fan, D.-P., Cheng, M.-M., Shen, J., & Shao, L. (2021) · Computational Visual Media · doi:10.1007/s41095-020-0199-z · Cited by 331
A Single Stream Network for Robust and Real-Time RGB-D Salient Object Detection
Zhao, X., Zhang, L., Pang, Y., Lu, H., & Zhang, L. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58542-6_39 · Cited by 259
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Wu, Y.-H., Liu, Y., Xu, J., Bian, J.-W., Gu, Y.-C., & Cheng, M.-M. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3134684 · Cited by 176
Metadata
- Authors
- Ju, R., Ge, L., Geng, W., Ren, T., & Wu, G.
- Venue
- 2014 IEEE International Conference on Image Processing (ICIP)
- Publisher
- IEEE
- Published
- 2014-10
- Pages
- 1115-1119
- ISSN
- 1522-4880 (ISSN-L)
- OpenAlex
- W1976409045
- Cited by
- 523
- References
- 0
- FWCI
- 7.03
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ju, R., Ge, L., Geng, W., Ren, T., & Wu, G. (2014). Depth saliency based on anisotropic center-surround difference. 2014 IEEE International Conference on Image Processing (ICIP). https://doi.org/10.1109/icip.2014.7025222
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