The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Attention-Guided Pyramid Context Networks for Detecting Infrared Small Target Under Complex Background
Abstract
Infrared small target detection techniques remain a challenging task due to the complex background. To overcome this problem, by exploring context information, this research presents a data-driven approach called attention-guided pyramid context network (AGPCNet). Specifically, we design attention-guided context block and perceive pixel correlations within and between patches at specific scales via local semantic association and global context attention, respectively. Then, the contextual information from multiple scales is fused by context pyramid module to achieve better feature representation. In the upsampling stage, we fuse the low and deep semantics through asymmetric fusion module to retain more information about small targets. The experimental results illustrate that AGPCNet has achieved state-of-the-art performance on three available infrared small target datasets.
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Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834
Squeeze-and-Excitation Networks
Hu, J., Shen, L., & Sun, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00745 · Cited by 35,667
Feature Pyramid Networks for Object Detection
Lin, T.-Y., Dollar, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.106 · Cited by 30,939
Squeeze-and-Excitation Networks
Hu, J., Shen, L., Albanie, S., Sun, G., & Wu, E. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2913372 · Cited by 12,157
Wang, X., Girshick, R., Gupta, A., & He, K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00813 · Cited by 11,596
Dual Attention Network for Scene Segmentation
Fu, J., Liu, J., Tian, H., Li, Y., Bao, Y., Fang, Z., & Lu, H. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00326 · Cited by 7,351
CCNet: Criss-Cross Attention for Semantic Segmentation
Huang, Z., Wang, X., Huang, L., Huang, C., Wei, Y., & Liu, W. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00069 · Cited by 3,045
GCNet: Non-Local Networks Meet Squeeze-Excitation Networks and Beyond
Cao, Y., Xu, J., Lin, S., Wei, F., & Hu, H. (2019) · 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) · doi:10.1109/iccvw.2019.00246 · Cited by 2,307
A Local Contrast Method for Small Infrared Target Detection
Chen, C. L. P., Li, H., Wei, Y., Xia, T., & Tang, Y. Y. (2014) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2013.2242477 · Cited by 1,351
Metadata
- Authors
- Zhang, T., Li, L., Cao, S., Pu, T., & Peng, Z.
- Venue
- IEEE Transactions on Aerospace and Electronic Systems
- Published
- 2023-08
- Volume
- 59
- Issue
- 4
- Pages
- 4250-4261
- ISSN
- 0018-9251 (ISSN-L)
- 1557-9603
- 2371-9877
- OpenAlex
- W4317794940
- Cited by
- 486
- References
- 35
- FWCI
- 59.67
- Type
- journal article
- Language
- en
- Open access
- closed
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