Siamese Visual Tracking With Residual Fusion Learning

doi:10.1109/access.2021.3134066

CIOMP OpenIR

	Siamese Visual Tracking With Residual Fusion Learning
	X. L. Sun; G. L. Han and L. H. Guo
	2022
发表期刊	Ieee Access
ISSN	2169-3536
卷号	10 页码:88421-88433
摘要	Multi-stage feature fusion is pretty effective for deep Siamese trackers to promote tracking performance. Unfortunately, conventional fusion approaches, such as weighted average, are so simple that they are inappropriate to combine the features with diverse characteristics. In addition, the fusion module is generally optimized along with Siamese network module, which may result in the performance degradation of the whole tracker. In this paper, we propose a novel feature fusion network for Siamese tracker by exploiting the expression capacity of residual fusion learning (SiamRFL). Specifically, the network employs the deep-layer features as direct input to semantically recognize the object from background, and refines the object state with local detail patterns by exploring the shallow-layer features through residual channel. The classification and the regression features can be fused respectively by deploying multiple fusion units. To avoid the degradation problem, we also present an ensemble training framework for our tracker, in which different loss functions are introduced to individually optimize the Siamese and the fusion modules. Compared to the baseline SiamRPN++ tracker, the proposed tracker achieves favorable gains by 0.696 -> 0.709, 0.285 -> 0.308, 0.603 -> 0.624, 0.496 -> 0.520 and 0.517 -> 0.559 on OTB100, VOT2019, UAV123, LaSOT and GOT1Ok datasets, outperforming other approaches by an obvious margin.
DOI	10.1109/access.2021.3134066
URL	查看原文
收录类别	sci ; ei
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/181722/67075
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	X. L. Sun,G. L. Han and L. H. Guo. Siamese Visual Tracking With Residual Fusion Learning[J]. Ieee Access,2022,10:88421-88433.
APA	X. L. Sun,&G. L. Han and L. H. Guo.(2022).Siamese Visual Tracking With Residual Fusion Learning.Ieee Access,10,88421-88433.
MLA	X. L. Sun,et al."Siamese Visual Tracking With Residual Fusion Learning".Ieee Access 10(2022):88421-88433.

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
Siamese Visual Track（4589KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载