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Sparse Coding with Multi-layer Decoders using Variance Regularization
Sparse coding with multi-layer decoders using variance regularization -
SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTA
Learning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream tasks. The proposed method learns sparse data... -
ShanghaiTech
The ShanghaiTech dataset includes 330 training and 107 test videos recorded at 13 different background locations.