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Parameter Hierarchical Optimization for Visible-Infrared Person Re-Identification
Importantly, in the alignment process of SAS and AAL, all the parameters are immediately optimized with optimization principles rather than training the whole network, which yields a better parameter training manner.
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.
Three-Stream Convolutional Networks for Video-based Person Re-Identification
This paper aims to develop a new architecture that can make full use of the feature maps of convolutional networks.
Reconstruction of Hidden Representation for Robust Feature Extraction
We believe that minimizing the reconstruction error of the hidden representation is more robust than minimizing the Frobenius norm of the Jacobian matrix of the hidden representation.
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