Fast camouflaged object detection via multi-scale feature-enhanced network-Reference-Cited by-同舟云学术

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Fast camouflaged object detection via multi-scale feature-enhanced network

Published:2024-02-28 Issue:4 Volume:18 Page:3903-3914
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Zhou Bingqin,Yang Kun,Gao Zhigang

Funder

Key Laboratories of Sensing and Application of Intelligent Optoelectronic System in Sichuan Provincial Universities

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-024-03051-1.pdf

Reference40 articles.

1. Chen, L.C., Papandreou, G., Kokkinos, I., et al.: Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834–848 (2017)

2. Chu, H.K., Hsu, W.H., Mitra, N.J., et al.: Camouflage images. ACM Trans Graph 29(4), 51–1 (2010)

3. Fan, D.P., Cheng, M.M., Liu, Y., et al.: Structure-measure: a new way to evaluate foreground maps. In: Proceedings of the IEEE international conference on computer vision, pp 4548–4557 (2017)

4. Fan, D.P., Gong, C., Cao, Y., et al.: Enhanced-alignment measure for binary foreground map evaluation. arXiv preprint arXiv:1805.10421 (2018)

5. Fan, D.P., Ji, G.P., Sun, G., et al.: Camouflaged object detection. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 2777–2787 (2020a)

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1. Boundary enhancement and refinement network for camouflaged object detection;Machine Vision and Applications;2024-08-03

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