Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Low-rank matrix recovery with structural incoherence for robust face recognition
Robust Face Recognition via Sparse Representation
An Approach for Restoring Occluded Images for Face-Recognition
Depth Enhancement via Low-Rank Matrix Completion
Transformed Schatten-1 Iterative Thresholding Algorithms for Low Rank Matrix Completion
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices
Recovery of Damped Exponentials Using Structured Low Rank Matrix Completion
Recovering low-rank matrices from few coefficients in any basis
Identity-Preserving Face Recovery from Portraits
Hybrid Histograms of Oriented Gradients-compressive sensing framework feature extraction for face recognition
Eigenfeature Regularization and Extraction in Face Recognition
RGB-D-Based Face Reconstruction and Recognition
Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably
Super-Resolution Method for Face Recognition Using Nonlinear Mappings on Coherent Features
Boosted Pre-loaded Mixture of Experts for low-resolution face recognition
From Rank-N to Rank-1 Face Recognition Based on Motion Similarity
Residual vs. Inception vs. Classical Networks for Low-Resolution Face Recognition
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
Optimal Local Basis: A Reinforcement Learning Approach for Face Recognition
Gabor-based kernel PCA with fractional power polynomial models for face recognition
A Mosaicing Scheme for Pose-Invariant Face Recognition
A Bayesian computer vision system for modeling human interactions
Deep learning: from chemoinformatics to precision medicine
Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning
Automatic Construction of Statechart-Based Anomaly Detection Models for Multi-Threaded SCADA via Spectral Analysis
Guided deep network for depth map super-resolution: How much can color help?