Multilinear Side-Information based Discriminant Analysis for face and kinship verification in the wild.

•We propose a novel method, Multilinear Side-Information based Discriminant Analysis (MSIDA), for dimensionality reduction and classification of tensor data.•On the face description level, we propose a new representation based on high order tensors. The proposed tensor representation is regarded as a new way for fusing local descriptors.•We empirically evaluate the proposed approach for face based identity and kinship verification on four challenging face benchmarks (LFW, Cornell KinFace, UB KinFace and TSkinface).