Multi-scale feature fusion network with FPN and attention mechanism for enhanced object detection

Hui Wang; Yu Wang; Jiamei Yang; Xinyou Li; Peng Zhou; Jianbin Zheng

doi:10.1117/12.3033518

16 October 2024 Multi-scale feature fusion network with FPN and attention mechanism for enhanced object detection

Hui Wang, Yu Wang, Jiamei Yang, Xinyou Li, Peng Zhou, Jianbin Zheng

Author Affiliations +

Proceedings Volume 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024); 132916I (2024) https://doi.org/10.1117/12.3033518
Event: Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 2024, Changchun, China

Abstract

Feature fusion is the process of combining information from different sources or different feature sets into a more comprehensive or informative feature set. Feature fusion is crucial because it can help to synthesize different levels of features to improve detection performance. In order to address the problem of imbalance between semantic and positional features due to the diversity of object scales in real complex scenes, the SSD algorithm is selected as the baseline to study a bi-directional feature pyramid structure based on path enhancement. This structure can fully fuse the semantic information of the deep feature maps and the positional information of the shallow ones. Considering different levels of feature maps have different resolutions and feature information contributes differently to the fusion, a lightweight attention mechanism is utilized for learning the weights of different features, which could effectively fuse features that are inconsistent in semantics and scale. Experimental results show that SSD300 and SSD512 network with feature fusion achieve 79.1% mAP and 81.0% mAP on the test set of PASCAL VOC 2007 dataset, respectively, which are 1.9% and 1.2% higher than the baseline, respectively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hui Wang, Yu Wang, Jiamei Yang, Xinyou Li, Peng Zhou, and Jianbin Zheng "Multi-scale feature fusion network with FPN and attention mechanism for enhanced object detection", Proc. SPIE 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 132916I (16 October 2024); https://doi.org/10.1117/12.3033518

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KEYWORDS

Feature fusion

Object detection

Visualization

Image processing

Feature extraction

Image fusion

Convolution

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