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Generalization of feature embeddings transferred from different video anomaly detection domains
By proposing novel cross-domain generalization measures, we study how source features can generalize for different target video domains, as well as analyze unsupervised transfer learning.
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis
The models are evaluated considering both the reconstruction error of the images and the feature spaces in terms of their discriminative power.
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