Towards robust subspace recovery via sparsity-constrained latent low-rank representation.

•We present a Sparse Latent Low-rank representation approach for robust visual recovery.•This approach constructs the dictionary using both observed and hidden data.•A low-rank representation with enhanced sparsity can be derived.•Extensive experiments have confirmed the superiority of the proposed method.