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Depth Enhanced Saliency Detection Method
Abstract
Human vision system understands the environment from 3D perception. However, most existing saliency detection algorithms detect the salient foreground based on 2D image information. In this paper, we propose a saliency detection method using the additional depth information. In our method, saliency cues are provided to follow the laws of the visually salient stimuli in both color and depth spaces. Simultaneously, the 'center bias' is also extended to 'spatial' bias to represent the nature advantage in 3D image. In addition, We build a dataset to test our method and the experiments demonstrate that the depth information is useful for extracting the salient object from the complex scenes.
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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
- Cheng, Y., Fu, H., Wei, X., Xiao, J., & Cao, X.
- Venue
- Proceedings of International Conference on Internet Multimedia Computing and Service
- Publisher
- ACM
- Published
- 2014-07-10
- Pages
- 23-27
- OpenAlex
- W1966025376
- Cited by
- 350
- References
- 0
- FWCI
- 3.78
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Depth Enhanced Saliency Detection Method. https://app.cochat.ai/papers/10.1145/2632856.2632866
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- Cheng, Y., Fu, H., Wei, X., Xiao, J., & Cao, X. (2014). Depth Enhanced Saliency Detection Method. Proceedings of International Conference on Internet Multimedia Computing and Service. https://doi.org/10.1145/2632856.2632866
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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