PKI-SSM: Prior Knowledge Integrated Self-supervised Model for Point Cloud Completing

Lingli Tang, Lei Liao, Jiachen Li, Yanchun Ma, Qing Xie, Yongjian Liu

Abstract: The self-supervised point cloud completion models are capable of training without the need for paired or complete point cloud data, relying solely on the incomplete point clouds themselves. However, it is precisely this advantage that limits the available information of the models, hindering their performance. Additionally, existing self-supervised methods focus more on designing consistency between partial point clouds and their various projection variants, while neglecting to explore complementary information and prior knowledge within the partial point clouds themselves.

External IDs:dblp:conf/icic/TangLLMXL25