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Remote Sensing Letters Volume 15, 2024 - Issue 5
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Research Letter

AFDet: alignment and focusing for aerial object detection

Yecheng LiangSchool of Communication Engineering, Jilin University, Changchun, Jilin, ChinaORCID Iconhttps://orcid.org/0000-0002-0707-2926View further author information
ORCID Icon,
Shigang WangSchool of Communication Engineering, Jilin University, Changchun, Jilin, ChinaCorrespondence[email protected]
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,
Meimei ChenSchool of Communication Engineering, Jilin University, Changchun, Jilin, ChinaView further author information
,
Jian WeiSchool of Communication Engineering, Jilin University, Changchun, Jilin, ChinaView further author information
&
Yan ZhaoSchool of Communication Engineering, Jilin University, Changchun, Jilin, ChinaView further author information
Pages 478-489 | Received 01 Jan 2023, Accepted 02 Jan 2024, Published online: 09 Apr 2024

References

  • Chen, Y., C. Han, N. Wang, and Z. Zhang. 2019. “Revisiting Feature Alignment for One-Stage Object Detection.” arXiv preprint arXiv:1908.01570.
  • Chen, Z., K. Chen, W. Lin, J. See, H. Yu, Y. Ke, and C. Yang. 2020. “Piou loss: Towards accurate oriented object detection in complex environments,” In European conference on computer vision, Springer, 195–211.
  • Ding, J., N. Xue, Y. Long, G. S. Xia, and Q. Lu. 2019. “Learning Roi Transformer for Oriented Object Detection in Aerial Images,” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2849–2858.
  • Girshick, R. 2015. “Fast r-cnn,” In Proceedings of the IEEE international conference on computer vision, 1440–1448.
  • Han, J., J. Ding, J. Li, and G. S. Xia. 2021. “Align deep features for oriented object detection.” IEEE Transactions on Geoscience & Remote Sensing 60:1–11. https://doi.org/10.1109/TGRS.2021.3062048.
  • Li, Y., Q. Huang, X. Pei, L. Jiao, and R. Shang. 2020. “Radet: Refine Feature Pyramid Network and Multi-Layer Attention Network for Arbitrary-Oriented Object Detection of Remote Sensing Images.” Remote Sensing 12 (3): Online. https://doi.org/10.3390/rs12030389.
  • Lin, T. Y., P. Goyal, R. Girshick, K. He, and P. Á. Doll. 2017. “Focal loss for dense object detection.” In Proceedings of the IEEE international conference on computer vision, 2980–2988.
  • Ma, J., W. Shao, H. Ye, L. Wang, H. Wang, Y. Zheng, and X. Xue. 2018. “Arbitrary-oriented scene text detection via rotation proposals.” IEEE Transactions on Multimedia 20 (11): 3111–3122. https://doi.org/10.1109/TMM.2018.2818020.
  • Qian, W., X. Yang, S. Peng, Y. Guo, and C. Yan. 2019. “Learning Modulated Loss for Rotated Object Detection.” CoRR abs/1911.08299. Online.
  • Redmon, J., and A. Farhadi. 2018. “Yolov3: An incremental improvement.” arXiv Preprint arXiv: 180402767.
  • Wang, J., W. Yang, H.-C. Li, H. Zhang, and G.-S. Xia. 2021. “Learning Center Probability Map for Detecting Objects in Aerial Images.” IEEE Transactions on Geoscience & Remote Sensing 59 (5): 4307–4323. https://doi.org/10.1109/TGRS.2020.3010051.
  • Xia, G.-S., X. Bai, J. Ding, Z. Zhu, S. Belongie, J. Luo, M. Datcu, M. Pelillo, and L. Zhang. 2018. “Dota: A large-scale dataset for object detection in aerial images,” In Proceedings of the IEEE conference on computer vision and pattern recognition, 3974–3983.
  • Xia, Z., X. Pan, S. Song, L. E. Li, and G. Huang. 2022. “Vision Transformer with Deformable Attention,” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 4794–4803.
  • Xu, Y., M. Fu, Q. Wang, Y. Wang, K. Chen, G.-S. Xia, and X. Bai. 2020. “Gliding Vertex on the Horizontal Bounding Box for Multi-Oriented Object Detection.” IEEE Transactions on Pattern Analysis & Machine Intelligence 43 (4): 1452–1459. https://doi.org/10.1109/TPAMI.2020.2974745.
  • Yang, X., and J. Yan. 2020. “Arbitrary-Oriented Object Detection with Circular Smooth Label,” In European Conference on Computer Vision. Springer, 677–694.
  • Yang, X., J. Yan, Z. Feng, and T. He. 2021. “R3det: Refined Single-Stage Detector with Feature Refinement for Rotating Object.” Proceedings of the AAAI Conference on Artificial Intelligence 35 (4): 3163–3171. https://doi.org/10.1609/aaai.v35i4.16426.
  • Yang, X., J. Yang, J. Yan, Y. Zhang, T. Zhang, Z. Guo, X. Sun, and K. Fu. 2019. “Scrdet: Towards More Robust Detection for Small, Cluttered and Rotated Objects,” In Proceedings of the IEEE/CVF International Conference on Computer Vision, 8232–8241.
  • Yang, X., Y. Zhou, G. Zhang, J. Yang, W. Wang, J. Yan, X. Zhang, and Q. Tian. 2022. “The Kfiou Loss for Rotated Object Detection.” arXiv Preprint arXiv: 220112558.
  • Yu, J., Y. Jiang, Z. Wang, Z. Cao, and T. Huang. 2016. “Unitbox: An Advanced Object Detection Network,” In Proceedings of the 24th ACM international conference on Multimedia, 516–520.
  • Zhang, G., S. Lu, and W. Zhang. 2019. “Cad-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery.” IEEE Transactions on Geoscience & Remote Sensing 57 (12): 10 015–10024. https://doi.org/10.1109/TGRS.2019.2930982.

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