The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Adaptive Fusion for RGB-D Salient Object Detection
Open accessAbstract
RGB-D (red, green, blue, and depth) salient object detection aims to identify the most visually distinctive objects in a pair of color and depth images. Based upon an observation that most of the salient objects may stand out at least in one modality, this paper proposes an adaptive fusion scheme to fuse saliency predictions generated from two modalities. Specifically, we design two-streamed convolutional neural networks (CNN), each of which extracts features and predicts a saliency map from either RGB or depth modality. Then, a saliency fusion module learns a switch map that is used to adaptively fuse the predicted saliency maps. A loss function composed of saliency supervision, switch map supervision, and edge-preserving constraints are designed to make full supervision, and the entire network is trained in an end-to-end manner. Benefited from the adaptive fusion strategy and the edge-preserving constraint, our approach outperforms state-of-the-art methods on three publicly available datasets.
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Cites
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Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148
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Global Contrast Based Salient Region Detection
Cheng, M.-M., Mitra, N. J., Huang, X., Torr, P. H. S., & Hu, S.-M. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2345401 · Cited by 2,463
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Saliency Optimization from Robust Background Detection
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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
JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection
Fu, K., Fan, D.-P., Ji, G.-P., & Zhao, Q. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00312 · Cited by 365
Hierarchical Alternate Interaction Network for RGB-D Salient Object Detection
Li, G., Liu, Z., Chen, M., Bai, Z., Lin, W., & Ling, H. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3062689 · Cited by 341
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
LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images
Zhou, W., Zhu, Y., Lei, J., Yang, R., & Yu, L. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3242775 · Cited by 298
Metadata
- Authors
- Wang, N., & Gong, X.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 55277-55284
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2907643346
- Cited by
- 258
- References
- 30
- FWCI
- 17.88
- Type
- journal article
- Language
- en
- Open access
- gold
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