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Found 2 papers, 0 papers with code
Deep Heterogeneous Hashing for Face Video Retrieval
To tackle the key challenge of hashing on the manifold, a well-studied Riemannian kernel mapping is employed to project data (i. e. covariance matrices) into Euclidean space and thus enables to embed the two heterogeneous representations into a common Hamming space, where both intra-space discriminability and inter-space compatibility are considered.
Hierarchical Disentangle Network for Object Representation Learning
In this paper, we propose the hierarchical disentangle network (HDN) to exploit the rich hierarchical characteristics among categories to divide the disentangling process in a coarse-to-fine manner, such that each level only focuses on learning the specific representations in its granularity and finally the common and unique representations in all granularities jointly constitute the raw object.
