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MSNet: A Deep Multi-scale Submanifold Network for Visual Classification
[article]
2022
arXiv
pre-print
The Symmetric Positive Definite (SPD) matrix has received wide attention as a tool for visual data representation in computer vision. Although there are many different attempts to develop effective deep architectures for data processing on the Riemannian manifold of SPD matrices, a very few solutions explicitly mine the local geometrical information in deep SPD feature representations. While CNNs have demonstrated the potential of hierarchical local pattern extraction even for SPD represented
arXiv:2201.10145v2
fatcat:pvgkpoatbrburdeqdzqb4nfoty