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Point cloud based retrieval for place recognition is an emerging problem invision field. The main challenge is how to find an efficient way to encode thelocal features into a discriminative global descriptor. In this paper, wepropose a Point Contextual Attention Network (PCAN), which can predict thesignificance of each local point feature based on point context. Our networkmakes it possible to pay more attention to the task-relevent features whenaggregating local features. Experiments on various benchmark datasets show thatthe proposed network can provide outperformance than current state-of-the-artapproaches.

PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval