Visual place recognition tasks often encounter significant challenges in
landmark detection due to the presence of irrelevant objects such as humans,
cars, and trees, despite the remarkable progress achieved by previous models,
especially in the context of transformers. To address this issue, we propose a
novel method that effectively leverages the strengths of vision transformers.
By employing a meticulous selection process, our approach identifies and
isolates specific patches within the image that correspond to occluding
objects. To evaluate the efficacy of our method, we created augmented datasets
and conducted comprehensive testing. The results demonstrate the superior
accuracy achieved by our proposed approach. This research contributes to the
advancement of landmark detection in visual place recognition and shows the
potential of leveraging vision transformers to overcome challenges posed by
cluttered real-world scenarios.

本研究提出了一种能够有效利用视觉 Transformer 的方法，通过精选和隔离图像中与遮挡物相对应的特定区域，以改进视觉地点识别中的地标检测问题，在拥挤的实际情境中显示了视觉 Transformer 的潜力，并证明了该方法的卓越准确性。