Deep low-rank feature learning and encoding for cross-age face recognition

M. Saad Shakeel1,2, Kin-Man Lam2
1School of Automation, Guangdong University of Petrochemical Technology, Maoming, China
2Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Tài liệu tham khảo

Ng, 2018, Orthogonal Filter Banks with region Log-Tied Rank covariance matrices for face recognition, J. Vis. Commun. Image Represent., 55, 548, 10.1016/j.jvcir.2018.07.002 Wang, 2020, Sparsity adaptive matching pursuit for face recognition, J. Vis. Commun. Image Represent., 67, 102764, 10.1016/j.jvcir.2020.102764 Sun, 2014, Deep learning face representation from predicting 10,000 classes, 1891 Wang, 2018, CosFace: Large margin cosine loss for deep face recognition, 5265 W. Liu, Y. Wen, Z. Yu, M. Li, B. Raj, L. Song, SphereFace: Deep Hypersphere Embedding for Face Recognition, in: IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 212-220. Deng, 2019, Arc Face: Additive angular margin loss for deep face recognition, 4690 Dodge, 2016, Understanding How Image Quality Affects Deep Neural Networks, 1 Wright, 2009, Robust face recognition via sparse representation, IEEE Trans. Pattern Anal. Mach. Intell, 31, 210, 10.1109/TPAMI.2008.79 Shakeel, 2019, Learning sparse discriminant low-rank features for low-resolution face recognition, J. Vis. Commun. Image Represent., 63 Simonyan, 2015, Very deep convolutional networks for large-scale image recognition Hardoon, 2004, J S-Taylor, Canonical correlation analysis: An overview with application to learning methods, Neural Comput., 16, 2639, 10.1162/0899766042321814 Shakeel, 2019, Deep feature encoding-based discriminative model for age-invariant face recognition, Pattern Recogn., 93, 442, 10.1016/j.patcog.2019.04.028 Zhang, 2017, Age Progression/Regression by Conditional Adversarial Autoencoder, 4838 Song, 2018, Dual Conditional GANs for Face Aging and Rejuvenation, In IJCA, I, 899 Gong, 2013, Hidden factor analysis for age invariant face recognition, 2872 Chen, 2015, Face Recognition and Retrieval using Cross-age reference coding with Cross-age celebrity Dataset, IEEE Trans. Multimedia, 17, 804, 10.1109/TMM.2015.2420374 Li, 2016, Aging face recognition: A Hierarchical learning model based on local patterns selection, IEEE Trans. Image Process., 25, 2146, 10.1109/TIP.2016.2535284 Wen, 2016, Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition, 4893 Bianco, 2017, Large Age-gap Face verification by Feature Injection in Deep Networks, Pattern Recogn. Lett., 90, 36, 10.1016/j.patrec.2017.03.006 Wang, 2017, Unleash the Black Magic in Age: a Multi-task Deep Neural Network Approach for Cross-age Face Verification, IEEE Int. Conf. Face. Gest. Recognition. Li, 2018, Age-Related Factor Guided Joint Task Modelling Convolutional Neural Network for Cross-Age Face Recognition, IEEE Trans. Inf. Forensics Security, 13, 2383, 10.1109/TIFS.2018.2819124 Wang, 2018, Orthogonal Deep Features Decomposition for Age-invariant Face Recognition Zhao, 2020, Towards Age-invariant Face Recognition, IEEE Trans. Pattern Anal. Mach. Intell. Li, 2018, Distance metric optimization driven convolutional neural network for age-invariant face recognition, Pattern Recogn., 75, 51, 10.1016/j.patcog.2017.10.015 Zhao, 2020, Disentangled representation learning and residual GAN for age-invariant face verification, Pattern Recogn., 100, 10.1016/j.patcog.2019.107097 L. Du, H. Hu, Y. Wu, Age factor removal network based on transfer learning and adversarial learning for cross-age face recognition, IEEE Trans. Circuits. Sys. Video. technology, (DOI: 10.1109/TCSVT.2019.2923262), 2019. Wang, 2019, Decorrelated adversarial learning for age-invariant face recognition Huang, 2021, A Parallel Architecture of Age Adversarial Convolutional Neural Network for Cross-Age Face Recognition, IEEE Trans. Circuits. Sys. Video. Technology, 31, 148, 10.1109/TCSVT.2020.2965739 F. J. Xu, K. Luu, M. Savvides, T.D. Bui, C.Y. Suen, Investigating Age invariant face recognition based on Periocular Biometrics, in: Int. Joint Conf. Biometrics, 2011, pp. 1–7. Facial Image Processing and Analysis (FIPA). FG-NET Aging Database. Available: http://fipa.cs.kit.edu/433.php#Downloads. Miller, 2010, Performance evaluation of local appearance based periocular recognition, in: Int Park, 2011, Periocular biometrics in the visible spectrum, IEEE Trans. Inf. Forensics Security, 6, 96, 10.1109/TIFS.2010.2096810 Chen, 2012, Low-Rank Matrix Recovery with Structural Incoherence for Robust Face Recognition, in, 2618 Jing, 2016, Multi-spectral low-rank structured dictionary learning for face recognition, Pattern Recogn., 59, 14, 10.1016/j.patcog.2016.01.023 Wu, 2016, Multi-view low-rank dictionary learning for image classification, Pattern Recogn., 50, 143, 10.1016/j.patcog.2015.08.012 Wang, 2019, Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification, IEEE Trans. Geoscience. Remote. Sens., 57, 911, 10.1109/TGRS.2018.2862899 Roweis, 2000, Nonlinear dimensionality reduction by locally linear embedding, Science, 290, 2323, 10.1126/science.290.5500.2323 Wang, 2010, Locality-constrained linear coding for image classification, 3360 Fu, 2017, Efficient locality-constrained occlusion coding for face recognition, Neurocomputing, 260, 104, 10.1016/j.neucom.2017.04.001 Bai, 2020, MFI: Multi-range Feature Interchange for Video Action Recognition Bentley, 1975, Multidimensional Binary Search Trees Used for Associative Searching, Comm. ACM, 18, 509, 10.1145/361002.361007 H. Zhou, K-W. Wong, K-M. Lam, Feature-aging for age-invariant face recognition, in: APSIPA, Dec. 2015, pp. 1-5. G. Koch, R. Zemel, R. Salakhutdinov, Siamese Neural Networks for one-shot image recognition, in ICML Workshops, 2015. Lin, 2011, Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation Meng, 2018, Zero-Shot learning via Low-Rank Representation based Manifold Regularization, IEEE Signal Process Lett., 25, 1379, 10.1109/LSP.2018.2857201 Tseng, 2001, Convergence of a Block Coordinate Descent method for Nondifferentiable Minimization, J. Optimizat. Theory Application, 109, 475, 10.1023/A:1017501703105 Pang, 2015, Local Laplacian coding from Theoretical Analysis of Local Coding Schemes for Locally Linear Classification, IEEE Trans. Cybern., 45, 2937, 10.1109/TCYB.2015.2433926 K. Ricanek, T. Tesafaye, MORPH: A longitudinal image database of normal adult age-progression, in: 7th FGR, 2006, pp. 341–345. Moschoglou, 2017, AgeDB: the first manually collected, in-the-wild age database Zhang, 2016, Joint face detection and alignment using multitask cascaded convolutional networks, IEEE Signal Process Lett., 23, 1499, 10.1109/LSP.2016.2603342 J. Deng, W. Dong, R. Socher, L-J. Li, K. Li, L.F. Fei, ImageNet: A Large-Scale Hierarchical Image Database, in: IEEE Conference on computer vision and pattern recognition, 2009. Viola, 2004, Robust real-time face detection, Int. J. Comput. Vision, 57, 137, 10.1023/B:VISI.0000013087.49260.fb Cao, 2013, Similarity metric learning for face recognition, in, 2408 Chen, 2013, Blessing of dimensionality: High-dimensional feature and its efficient compression for face verification, 3025 Liu, 2010, Robust subspace segmentation by low-rank representation, 663