4 accepted papers
Single-stream architectures using Vision Transformer (ViT) backbones show great potential for real-time UAV tracking recently. However, frequent occlusions from obstacles like buildings and trees expose a major drawback: these models often lack strategies to handle occlusions effectively. New method…
Harnessing low-light enhancement and domain adaptation, nighttime UAV tracking has made substantial strides. However, over-reliance on image enhancement, limited high-quality nighttime data, and a lack of integration between daytime and nighttime trackers hinder the development of an end-to-end trai
Harnessing transformer-based models, visual tracking has made substantial strides. However, the sluggish performance of current trackers limits their practicality on devices with constrained computational capabilities, especially for real-time unmanned aerial vehicle (UAV) tracking. Addressing this…
While discriminative correlation filters (DCF)-based trackers prevail in UAV tracking for their favorable efficiency, lightweight convolutional neural network (CNN)-based trackers using filter pruning have also demonstrated remarkable efficiency and precision. However, the use of pure vision transfo…