The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Boundary-Guided Camouflaged Object Detection
Open accessAbstract
Camouflaged object detection (COD), segmenting objects that are elegantly blended into their surroundings, is a valuable yet challenging task. Existing deep-learning methods often fall into the difficulty of accurately identifying the camouflaged object with complete and fine object structure. To this end, in this paper, we propose a novel boundary-guided network (BGNet) for camouflaged object detection. Our method explores valuable and extra object-related edge semantics to guide representation learning of COD, which forces the model to generate features that highlight object structure, thereby promoting camouflaged object detection of accurate boundary localization. Extensive experiments on three challenging benchmark datasets demonstrate that our BGNet significantly outperforms the existing 18 state-of-the-art methods under four widely-used evaluation metrics. Our code is publicly available at: https://github.com/thograce/BGNet.
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Cites
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., & Hu, Q. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01155 · Cited by 9,641 · cited 1×
“To enhance feature representation, inspired by [Wang et al., 2020], we introduce local attention to explore critical feature channels.”
MethodRes2Net: A New Multi-Scale Backbone Architecture
Gao, S.-H., Cheng, M.-M., Zhao, K., Zhang, X.-Y., Yang, M.-H., & Torr, P. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2938758 · Cited by 3,385
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
PraNet: Parallel Reverse Attention Network for Polyp Segmentation
Fan, D.-P., Ji, G.-P., Zhou, T., Chen, G., Fu, H., Shen, J., & Shao, L. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-59725-2_26 · Cited by 1,499
EGNet: Edge Guidance Network for Salient Object Detection
Zhao, J., Liu, J.-J., Fan, D.-P., Cao, Y., Yang, J., & Cheng, M.-M. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00887 · Cited by 1,202
How to Evaluate Foreground Maps
Margolin, R., Zelnik-Manor, L., & Tal, A. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.39 · Cited by 1,106
A Simple Pooling-Based Design for Real-Time Salient Object Detection
Liu, J.-J., Hou, Q., Cheng, M.-M., Feng, J., & Jiang, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00404 · Cited by 1,100
F³Net: Fusion, Feedback and Focus for Salient Object Detection
Wei, J., Wang, S., & Huang, Q. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6916 · Cited by 1,050
Self-citationFan, D.-P., Ji, G.-P., Sun, G., Cheng, M.-M., Shen, J., & Shao, L. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00285 · Cited by 896
Metadata
- Authors
- Sun, Y., Wang, S., Chen, C., & Xiang, T.-Z.
- Venue
- Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
- Published
- 2022-07
- Pages
- 1335-1341
- OpenAlex
- W4285601297
- Cited by
- 336
- References
- 33
- FWCI
- 26.08
- Type
- conference paper
- Language
- en
- Open access
- bronze
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