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唐乾坤, 胡瑜. 基于注意力机制的单阶段目标检测锚点框部件感知特征表达[J]. 计算机辅助设计与图形学学报, 2020, 32(8): 1293-1304. DOI: 10.3724/SP.J.1089.2020.18046
引用本文: 唐乾坤, 胡瑜. 基于注意力机制的单阶段目标检测锚点框部件感知特征表达[J]. 计算机辅助设计与图形学学报, 2020, 32(8): 1293-1304. DOI: 10.3724/SP.J.1089.2020.18046
Tang Qiankun, Hu Yu. Attention Based Part-Aware Features of Anchor Boxes for Single-Shot Object Detection[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(8): 1293-1304. DOI: 10.3724/SP.J.1089.2020.18046
Citation: Tang Qiankun, Hu Yu. Attention Based Part-Aware Features of Anchor Boxes for Single-Shot Object Detection[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(8): 1293-1304. DOI: 10.3724/SP.J.1089.2020.18046

基于注意力机制的单阶段目标检测锚点框部件感知特征表达

Attention Based Part-Aware Features of Anchor Boxes for Single-Shot Object Detection

  • 摘要: 针对现有单阶段目标检测算法锚点框特征表达不足影响检测精度的问题,提出了一种增强锚点框特征表达的算法,其包含注意力机制模块和部件感知模块.首先,注意力机制模块根据各个锚点框的不同属性自适应地提供不同的特征表达.然后,部件感知模块准确地提取各个锚点框内部的判别性部件特征以作为各个锚点框进行预测所需的特有特征.将所提设计与现有SSD算法结合并在多个公开的目标检测数据集上进行实验,结果表明,所提算法能够显著提高单阶段目标检测算法的精度并维持实时运行速度(14 ms);进一步地,在扩展实验上的结果表明,所提算法也能够改善生成的区域建议框的召回率及两阶段目标检测算法的精度.

     

    Abstract: In this paper,we propose a lightweight but effective design to enhance the anchor representations for improving the performance of single-shot object detectors.This design consists of an attention module and a part-aware module.First,an attention module is applied for a location to adaptively express various representations based on the targets of the anchor boxes covering the location.The part-aware module further extracts the discriminative part features inside each anchor box as its individual features for robust prediction.Assembling the proposed modules to the SSD,our method is able to consistently boost the performance on several public benchmarks while maintaining real-time inference speed(14 ms).Extensive experiments on the region proposal generation indicate that the proposed method also promotes the recall of region proposals,so as the accuracy of two-stage object detection.

     

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