Visual Place Recognition (VPR) is generally concerned with localizing outdoor
images. However, localizing indoor scenes that contain part of an outdoor scene
can be of large value for a wide range of applications. In this paper, we
introduce Inside Out Visual Place Recognition (IOVPR), a task aiming to
localize images based on outdoor scenes visible through windows. For this task
we present the new large-scale dataset Amsterdam-XXXL, with images taken in
Amsterdam, that consists of 6.4 million panoramic street-view images and 1000
user-generated indoor queries. Additionally, we introduce a new training
protocol Inside Out Data Augmentation to adapt Visual Place Recognition methods
for localizing indoor images, demonstrating the potential of Inside Out Visual
Place Recognition. We empirically show the benefits of our proposed data
augmentation scheme on a smaller scale, whilst demonstrating the difficulty of
this large-scale dataset for existing methods. With this new task we aim to
encourage development of methods for IOVPR. The dataset and code are available
for research purposes at this https URL

本文介绍了室内外视觉定位的新任务 Inside Out Visual Place Recognition (IOVPR)，提出室内景观中的大窗户可以提供室外场景信息，因此可以使用 Visual Place Recognition 方法进行定位。通过引入室内外数据扩充方法，改进了现有的 Visual Place Recognition 方法以适应室内场景的环境，最后，使用大规模的 Amsterdam-XXXL 数据集进行验证。