X. Deng, L. Liao, P. Jiang and Y. Qian, "Towards Scale Adaptive Underwater Detection Through Refined Pyramid Grid," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10094683. (CCF B类)
发布时间：2024-03-13
点击次数：
发表刊物：2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
摘要：Abstract:Most object detection methods have achieved impressive performance on several public benchmarks, instead, facing underwater detection tasks, it is challenging to detect marine targets because of the inherent illumination inhomogeneity in underwater images. Moreover, the imbalanced foreground-background proposals further aggravate the situation of capturing marine organisms. To address the problems, we analyze the deficiency of existing feature pyramid structures and propose a multi-depth and multi-breadth pyramid architecture named Refined Pyramid Grid (RPG). A Harmonizing Focal Loss (HFL) is then proposed to generalize the discrete labels in focal loss to the continuous version to improve the optimization. Experimental results on the real-world datasets have demonstrated the efficiency and reliability of the proposed framework regarding underwater object detection tasks.
备注：http://faculty.csu.edu.cn/dengxiaoheng/zh_CN/lwcg/10445/content/49293.htm
是否译文：否
附件：
16-Towards scale adaptive underwater detection through refined pyramid grid.pdf
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