Cross-Shape Attention for Part Segmentation of 3D Point Clouds

Marios Loizou, Siddhant Garg, Dmitrii M Petrov, Melinos Averkiou, Evangelos Kalogerakis

Abstract: We present a method that propagates point-wise feature representations across shapes within a collection for the purpose of 3D shape segmentation. This is achieved through a cross-shape attention operation that assesses the degree of interaction between points on different shapes and mediates feature propagation. For each test shape, our method finds shapes in an input collection that are suited for executing such cross-shape attention operations. The resulting point-wise feature representations lead to more consistent 3D shape segmentation results, as demonstrated in our experiments.