@inproceedings{de037a1a230f46099e6ca816ea493084,
title = "Siamese Dual Path Aggregation Network for Object Tracking",
abstract = "Siamese trackers have attracted great attention on visual object tracking due to their real-time speed and high accuracy. In this paper, we propose a dual path aggregation network (SiamDPAN) for high-performance tracking. First, we build a multi-level similarity maps aggregation (MSA) structure, which predicts and fuses the similarity maps from multi-level features. Second, we propose a mask path aggregation module (MPA) for better capturing the appearance changes of objects by propagating maps in low-layers. We conduct sufficient ablation studies to demonstrate the effectiveness of our proposed tracker. We only train our network with two datasets, achieving 0.436 EAO and 0.351 EAO on VOT2016 and VOT2018.",
keywords = "Mask path aggregation, Multi-level similarity maps aggregation, Siamese trackers",
author = "Yijun Tian and Huiqian Du and Zhifeng Ma",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; 13th International Conference on Graphics and Image Processing, ICGIP 2021 ; Conference date: 18-08-2021 Through 20-08-2021",
year = "2022",
doi = "10.1117/12.2623408",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Liang Xiao and Dan Xu",
booktitle = "Thirteenth International Conference on Graphics and Image Processing, ICGIP 2021",
address = "United States",
}