文献类型：期刊文献

英文题名：Efficient Visual Object Tracking withTemporal Context-Aware Token Learning andScale Adaptive Token Pruning

作者：Gui, Yan[1]; Ou, Yiru[1]; Guo, Ruojun[1]; Zhang, Jianming[1]; Chen, Zhihua[2]

机构：[1] School of Computer and Communication Engineering, Changsha University of Science and Technology, Hunan, Changsha, 410076, China; [2] Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, Shanghai, 200237, China

年份：2026

卷号：2297 CCIS

起止页码：361

外文期刊名：Communications in Computer and Information Science

收录：EI(收录号：20253118905504)

语种：英文

外文关键词：Computer vision - Object tracking - Target tracking

摘要：Transformer-based trackers have recently demonstrated remarkable performance in the visual tracking community. However, leveraging rich information across temporal frames is difficult for conventional visual Transformers due to the quadratically increasing complexity of the self-attention computation, thus limiting the performance potential of Transformer-based trackers. In this paper, we propose a more efficient one-stream tracking framework by integrating temporal context-aware token learning and scale-adaptive token pruning. Specifically, we employ a temporal context-aware encoder that simultaneously enhances feature learning and relation modeling by mutually interacting the inherent template, dynamic templates, and the search region solely through self-attention. To balance the tracking accuracy and speed, a scale-adaptive token pruning module is proposed based on learnable scale attention, thus making the search token pruning more adaptable to different target scales. Furthermore, to handle multiple templates during inference and improve tracking robustness, we design a temporal template updating strategy that dynamically selects the templates capturing appearance variations of target objects. The results on five benchmarks show that our tracker obtains superior tracking performance while maintaining fast inference speed. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.