  Point cloud based retrieval for place recognition is an emerging problem in
vision field. The main challenge is how to find an efficient way to encode the
local features into a discriminative global descriptor. In this paper, we
propose a Point Contextual Attention Network (PCAN), which can predict the
significance of each local point feature based on point context. Our network
makes it possible to pay more attention to the task-relevent features when
aggregating local features. Experiments on various benchmark datasets show that
the proposed network can provide outperformance than current state-of-the-art
approaches.
