  In this paper, we propose a graph-based kinship reasoning (GKR) network for
kinship verification, which aims to effectively perform relational reasoning on
the extracted features of an image pair. Unlike most existing methods which
mainly focus on how to learn discriminative features, our method considers how
to compare and fuse the extracted feature pair to reason about the kin
relations. The proposed GKR constructs a star graph called kinship relational
graph where each peripheral node represents the information comparison in one
feature dimension and the central node is used as a bridge for information
communication among peripheral nodes. Then the GKR performs relational
reasoning on this graph with recursive message passing. Extensive experimental
results on the KinFaceW-I and KinFaceW-II datasets show that the proposed GKR
outperforms the state-of-the-art methods.
