计算机工程2025，Vol.51Issue(6)：93-101,9.DOI:10.19678/j.issn.1000-3428.0069350
基于显著目标追踪的行为检测方法
Action Detection Method Based on Salient Target Tracking
摘要
Abstract
Action detection comprises both action classification and boundary localization,with a predominant focus on action and boundary features.Current methods neglect the significance of spatial features in this task and suffer from ambiguous action boundary prediction,which affects the performance and application of action detection models.To address these challenges,this paper proposes a Salient Object Tracking-based Action Detection(SOT-AD)method.First,to learn salient spatial information at different scales,a hierarchical attention network is introduced to capture salient objects associated with actions,while reducing interference from action-irrelevant information.Second,to ensure consistency in salient object attention across adjacent temporal positions,this paper proposes a salient object tracking loss.Neutral samples are introduced to construct a"target-sub-target-background"feature pool to learn temporal contextual information for feature sequences,which facilitates the realization of salient object tracking.Experimental results on two widely used datasets,THUMOS14 and ActivityNet1.3,demonstrate that SOT-AD outperforms mainstream methods with improvements of 0.9 percentage points and 0.6 percentage points in terms of mean Average Precision(mAP),respectively.Notably,on the THUMOS14 dataset,SOT-AD achieves an mAP@0.5 of 72.7％.关键词
行为检测/注意力机制/噪声对比损失/行为追踪/特征金字塔Key words
Action Detection(AD)/attention mechanism/noise contrast loss/action tracking/feature pyramid分类
计算机与自动化引用本文复制引用
单鹏畅,高利剑,董文龙,毛启容..基于显著目标追踪的行为检测方法[J].计算机工程,2025,51(6):93-101,9.基金项目
江苏省重点研发计划(BE2020036) （BE2020036）
江苏省研究生科研与实践创新计划项目(KYCX23_3675) （KYCX23_3675）
江苏大学应急管理学院专项科研项目(KY-A-01). （KY-A-01）
