We propose a novel Siamese Natural Language Tracker (SNLT), which brings the
advancements in visual tracking to the tracking by natural language (NL)
descriptions task. The proposed SNLT is applicable to a wide range of Siamese
trackers, providing a new class of baselines for the tracking by NL task and
promising future improvements from the advancements of Siamese trackers. The
carefully designed architecture of the Siamese Natural Language Region Proposal
Network (SNL-RPN), together with the Dynamic Aggregation of vision and language
modalities, is introduced to perform the tracking by NL task. Empirical results
over tracking benchmarks with NL annotations show that the proposed SNLT
improves Siamese trackers by 3 to 7 percentage points with a slight tradeoff of
speed. The proposed SNLT outperforms all NL trackers to-date and is competitive
among state-of-the-art real-time trackers on LaSOT benchmarks while running at
50 frames per second on a single GPU.

提出 “Siamese Natural Language Tracker” 的新方法，应用于自然语言描述任务的跟踪。相关实验证明，该算法比 “Siamese trackers” 有显著提升，是目前最好的实时跟踪器之一。