Visual Tracking with FPN Based on Transformer and Response Map Enhancement

doi:10.3390/app12136551

CIOMP OpenIR

	Visual Tracking with FPN Based on Transformer and Response Map Enhancement
	A. P. Deng; J. H. Liu; Q. Q. Chen; X. Wang and Y. J. Zuo
	2022
发表期刊	Applied Sciences-Basel
卷号	12 期号:13 页码:16
摘要	Siamese network-based trackers satisfy the balance between performance and efficiency for visual tracking. However, they do not have enough robustness to handle the challenges of target occlusion and similar objects. In order to improve the robustness of the tracking algorithm, this paper proposes visual tracking with FPN based on Transformer and response map enhancement. In this paper, a feature pyramid structure based on Transformer is designed to encode robust target-specific appearance features, as well as the response map enhanced module to improve the tracker's ability to distinguish object and background. Extensive experiments and ablation experiments are conducted on many challenging benchmarks such as UAV123, GOT-10K, LaSOT and OTB100. These results show that the tracking algorithm we proposed in this paper can effectively improve the tracking robustness against the challenges of target occlusion and similar object, and thus improve the precision rate and success rate of the tracking algorithm.
DOI	10.3390/app12136551
URL	查看原文
收录类别	sci
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67234
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	A. P. Deng,J. H. Liu,Q. Q. Chen,et al. Visual Tracking with FPN Based on Transformer and Response Map Enhancement[J]. Applied Sciences-Basel,2022,12(13):16.
APA	A. P. Deng,J. H. Liu,Q. Q. Chen,&X. Wang and Y. J. Zuo.(2022).Visual Tracking with FPN Based on Transformer and Response Map Enhancement.Applied Sciences-Basel,12(13),16.
MLA	A. P. Deng,et al."Visual Tracking with FPN Based on Transformer and Response Map Enhancement".Applied Sciences-Basel 12.13(2022):16.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Visual Tracking with（5930KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载