Optics and Precision Engineering, Volume. 28, Issue 10, 2311(2020)
Exploring aligned latent representations for cross-domain face recognition
[1] [1] CAO B, WANG N N, GAO X B, et al.. Multi-margin based decorrelation learning for heterogeneous face recognition[C]. International Joint Conference on Artificial Intelligence, 2019: 680-686.
CAO B, WANG N N, GAO X B, et al.. Multi-margin based decorrelation learning for heterogeneous face recognition[C]. International Joint Conference on Artificial Intelligence, 2019: 680-686.
[3] [3] WU X, HUANG H B, PATEL V M, et al.. Disentangled variational representation for heterogeneous face recognition[C]. Thirty-third AAAI Conference on Artificial Intelligence, 2019: 9005-9012.
WU X, HUANG H B, PATEL V M, et al.. Disentangled variational representation for heterogeneous face recognition[C]. Thirty-third AAAI Conference on Artificial Intelligence, 2019: 9005-9012.
[4] [4] HE R, WU X, SUN Z N, et al.. Wasserstein CNN: Learning invariant features for nir-vis face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 41(7): 1761-1773.
HE R, WU X, SUN Z N, et al.. Wasserstein CNN: Learning invariant features for nir-vis face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 41(7): 1761-1773.
[5] [5] WU X, SONG L X, HE R, et al.. Coupled deep learning for heterogeneous face recognition[C]. Thirty-second AAAI Conference on Artificial Intelligence, 2018.
WU X, SONG L X, HE R, et al.. Coupled deep learning for heterogeneous face recognition[C]. Thirty-second AAAI Conference on Artificial Intelligence, 2018.
[6] [6] OLIVEIRA J S, SOUZA G B, ROCHA A R, et al.. Cross-domain deep face matching for real banking security systems[C]. arXiv preprint: 1806.07644, 2018.
OLIVEIRA J S, SOUZA G B, ROCHA A R, et al.. Cross-domain deep face matching for real banking security systems[C]. arXiv preprint: 1806.07644, 2018.
[7] [7] HE R, CAO J, SONG L X, et al.. Cross-spectral face completion for nir-vis heterogeneous face recognition[C]. arXiv preprint: 1902.03565, 2019.
HE R, CAO J, SONG L X, et al.. Cross-spectral face completion for nir-vis heterogeneous face recognition[C]. arXiv preprint: 1902.03565, 2019.
[8] [8] ZHANG T, WANG H, DONG Q L. Deep disentangling siamese network for frontal face synthesis under neutral illumination[J]. IEEE Signal Processing Letters, 2018, 25(9): 1344-1348.
ZHANG T, WANG H, DONG Q L. Deep disentangling siamese network for frontal face synthesis under neutral illumination[J]. IEEE Signal Processing Letters, 2018, 25(9): 1344-1348.
[10] [10] GOODFELLOW I, JEAN P A, MIRZA M, et al.. Generative adversarial nets[C]. Conference and Workshop on Neural Information Processing Systems, 2014: 2672-2680.
GOODFELLOW I, JEAN P A, MIRZA M, et al.. Generative adversarial nets[C]. Conference and Workshop on Neural Information Processing Systems, 2014: 2672-2680.
[11] [11] KINGMA D P, WELLING M. Auto-encoding variational bayes[C]. International Conference on Machine Learning, 2013.
KINGMA D P, WELLING M. Auto-encoding variational bayes[C]. International Conference on Machine Learning, 2013.
[12] [12] HUANG H B, HE R, SUN Z N, et al.. Introvae: Introspective variational autoencoders for photographic image synthesis[C]. Conference and Workshop on Neural Information Processing Systems, 2018: 52-63.
HUANG H B, HE R, SUN Z N, et al.. Introvae: Introspective variational autoencoders for photographic image synthesis[C]. Conference and Workshop on Neural Information Processing Systems, 2018: 52-63.
[13] [13] SUN H Z, XU W D, DENG C, et al.. Multi-digit image synthesis using recurrent conditional variational autoencoder[C]. International Joint Conference on Neural Networks, 2016: 375-380.
SUN H Z, XU W D, DENG C, et al.. Multi-digit image synthesis using recurrent conditional variational autoencoder[C]. International Joint Conference on Neural Networks, 2016: 375-380.
[14] [14] WANG W R, ARORA R, LIVERSCU K, et al.. On deep multi-view representation learning[C]. International Conference on Machine Learning, 2015: 1083-1092.
WANG W R, ARORA R, LIVERSCU K, et al.. On deep multi-view representation learning[C]. International Conference on Machine Learning, 2015: 1083-1092.
[15] [15] KAN M N, SHAN S G, ZHANG H H, et al.. Multi-view discriminant analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 38(1): 188-194.
KAN M N, SHAN S G, ZHANG H H, et al.. Multi-view discriminant analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 38(1): 188-194.
[16] [16] WANG N, GAO X, SUN L, et al.. Bayesian face sketch synthesis[J]. IEEE Transactions on Image Processing, 2017, 26 (3): 1264-1274.
WANG N, GAO X, SUN L, et al.. Bayesian face sketch synthesis[J]. IEEE Transactions on Image Processing, 2017, 26 (3): 1264-1274.
[17] [17] TRAN L, YIN X, LIU X M. Disentangled representation learning gan for pose-invariant face recognition[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2017: 1415-1424.
TRAN L, YIN X, LIU X M. Disentangled representation learning gan for pose-invariant face recognition[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2017: 1415-1424.
[18] [18] QIAN Y, DENG W, HU J. Unsupervised face normalization with extreme pose and expression in the wild[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2019: 9851-9858.
QIAN Y, DENG W, HU J. Unsupervised face normalization with extreme pose and expression in the wild[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2019: 9851-9858.
[19] [19] HE M, ZHANG J, SHAN S, et al.. Deformable face net for pose invariant face recognition[J]. Pattern Recognition, 2020, 100: 10711.
HE M, ZHANG J, SHAN S, et al.. Deformable face net for pose invariant face recognition[J]. Pattern Recognition, 2020, 100: 10711.
[20] [20] FAN L L, ZHAO H W, ZHAO H Y, et al.. Survey of target detection based on deep convolutional neural networks [J]. Opt. Precision Eng., 2020, 28(5): 1153-1164. (in Chinese)
FAN L L, ZHAO H W, ZHAO H Y, et al.. Survey of target detection based on deep convolutional neural networks [J]. Opt. Precision Eng., 2020, 28(5): 1153-1164. (in Chinese)
[21] [21] HOU X X, SHEN L L, SUN K, et al.. Deep feature consistent variational autoencoder[C]. Winter Conference on Applications of Computer Vision, 2017: 1133-1141.
HOU X X, SHEN L L, SUN K, et al.. Deep feature consistent variational autoencoder[C]. Winter Conference on Applications of Computer Vision, 2017: 1133-1141.
[22] [22] GROSS R, MATTHEWS I, COHN J, et al.. Multi-pie[J]. Image and Vision Computing, 2010, 28(5): 807-813.
GROSS R, MATTHEWS I, COHN J, et al.. Multi-pie[J]. Image and Vision Computing, 2010, 28(5): 807-813.
[23] [23] LI S, YI D, LEI Z, et al.. The casia nir-vis 2.0 face database[C]. IEEE Conference on Computer Vision and Pattern Recognition workshops, 2013: 348-353.
LI S, YI D, LEI Z, et al.. The casia nir-vis 2.0 face database[C]. IEEE Conference on Computer Vision and Pattern Recognition workshops, 2013: 348-353.
[24] [24] ZHU Z Y, LUO P, WANG X G, et al.. Deep learning identity-preserving face space[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 113-120.
ZHU Z Y, LUO P, WANG X G, et al.. Deep learning identity-preserving face space[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2013: 113-120.
[25] [25] ZHU Z Y, LUO P, WANG X G, et al.. Multi-view perceptron: a deep model for learning face identity and view representations[C]. Conference and Workshop on Neural Information Processing Systems, 2014: 217-225.
ZHU Z Y, LUO P, WANG X G, et al.. Multi-view perceptron: a deep model for learning face identity and view representations[C]. Conference and Workshop on Neural Information Processing Systems, 2014: 217-225.
[26] [26] YIM J, JUNG H, YOO B, et al.. Rotating your face using multi-task deep neural network[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 676-684.
YIM J, JUNG H, YOO B, et al.. Rotating your face using multi-task deep neural network[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 676-684.
[27] [27] HU Y B, WU X, YU B, et al.. Pose-guided photorealistic face rotation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2018: 8398-8406.
HU Y B, WU X, YU B, et al.. Pose-guided photorealistic face rotation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2018: 8398-8406.
[28] [28] HUANG X S, LEI Z, FAN M Y, et al.. Regularized discriminative spectral regression method for heterogeneous face matching[J]. IEEE Transactions on Image Processing, 2012, 22(1): 353-362.
HUANG X S, LEI Z, FAN M Y, et al.. Regularized discriminative spectral regression method for heterogeneous face matching[J]. IEEE Transactions on Image Processing, 2012, 22(1): 353-362.
[29] [29] YI D, LEI Z, LI S Z. Shared representation learning for heterogenous face recognition[C]. IEEE international conference and workshops on automatic face and gesture recognition, 2015: 1-7.
YI D, LEI Z, LI S Z. Shared representation learning for heterogenous face recognition[C]. IEEE international conference and workshops on automatic face and gesture recognition, 2015: 1-7.
[30] [30] REALE C, NASRABADI N M, KWON H, et al.. Seeing the forest from the trees: A holistic approach to near-infrared heterogeneous face recognition[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 54-62.
REALE C, NASRABADI N M, KWON H, et al.. Seeing the forest from the trees: A holistic approach to near-infrared heterogeneous face recognition[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2016: 54-62.
[31] [31] SONG L, ZHANG M, WU X, et al.. Adversarial discriminative heterogeneous face recognition[C]. International Joint Conference on Artificial Intelligence, 2018.
SONG L, ZHANG M, WU X, et al.. Adversarial discriminative heterogeneous face recognition[C]. International Joint Conference on Artificial Intelligence, 2018.
[33] [33] PENG C, WANG N, LI J, et al.. Re-ranking high-dimensional deep local representation for NIR-VIS face recognition[J]. IEEE Transactions on Image Processing, 2019, 28(9): 4553-4565.
PENG C, WANG N, LI J, et al.. Re-ranking high-dimensional deep local representation for NIR-VIS face recognition[J]. IEEE Transactions on Image Processing, 2019, 28(9): 4553-4565.
[34] [34] MESSER K, KITTLER J, SADEGHI M, et al.. Face verification competition on the XM2VTS database[C]. International Conference on Audio-and Video-Based Biometric Person Authentication, Springer, 2003: 964-974.
MESSER K, KITTLER J, SADEGHI M, et al.. Face verification competition on the XM2VTS database[C]. International Conference on Audio-and Video-Based Biometric Person Authentication, Springer, 2003: 964-974.
[35] [35] ZHANG M, WANG N, GAO X, et al.. Markov Random Neural Fields for Face Sketch Synthesis[C]. International Joint Conference on Artificial Intelligence, 2018: 1142-1148.
ZHANG M, WANG N, GAO X, et al.. Markov Random Neural Fields for Face Sketch Synthesis[C]. International Joint Conference on Artificial Intelligence, 2018: 1142-1148.
[36] [36] SONG Y, BAO L, YANG Q, et al.. Real-time exemplar-based face sketch synthesis[C]. European Conference on Computer Vision, Springer, 2014: 800-813.
SONG Y, BAO L, YANG Q, et al.. Real-time exemplar-based face sketch synthesis[C]. European Conference on Computer Vision, Springer, 2014: 800-813.
[37] [37] WANG N, GAO X, LI J. Random sampling for fast face sketch synthesis[J]. Pattern Recognition, 2018, 76(1): 215-227.
WANG N, GAO X, LI J. Random sampling for fast face sketch synthesis[J]. Pattern Recognition, 2018, 76(1): 215-227.
[38] [38] ZHANG L, LIN L, WU X, et al.. End-to-end photo-sketch generation via fully convolutional representation learning[C]. The 5th ACM on International Conference on Multimedia Retrieval, ACM Press, 2015: 627-634.
ZHANG L, LIN L, WU X, et al.. End-to-end photo-sketch generation via fully convolutional representation learning[C]. The 5th ACM on International Conference on Multimedia Retrieval, ACM Press, 2015: 627-634.
[39] [39] GOODFELLOW I, POUGET-ADADIE J, MIRZA M, et al.. Generative adversarial nets[C]. Advances in neural information processing systems, MIT Press, 2014: 2672-2680.
GOODFELLOW I, POUGET-ADADIE J, MIRZA M, et al.. Generative adversarial nets[C]. Advances in neural information processing systems, MIT Press, 2014: 2672-2680.
[40] [40] ZHU J Y, PARK T, ISOLA P, et al.. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]. IEEE Conference on Computer Vision and Pattern Recognition, Piscataway: IEEE, 2017: 2223-2232.
ZHU J Y, PARK T, ISOLA P, et al.. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]. IEEE Conference on Computer Vision and Pattern Recognition, Piscataway: IEEE, 2017: 2223-2232.
[41] [41] YI Z, ZHANG H, TAN P, et al.. Dualgan: Unsupervised dual learning for image-to-image translation[C]. IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 2017: 2849-2857.
YI Z, ZHANG H, TAN P, et al.. Dualgan: Unsupervised dual learning for image-to-image translation[C]. IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 2017: 2849-2857.
[42] [42] KANCHARAGUNTA K B, DUBEY S R. Csgan: cyclic-synthesized generative adversarial networks for image-to-image transformation[J]. arXiv preprint arXiv: 1901.03554, 2019.
KANCHARAGUNTA K B, DUBEY S R. Csgan: cyclic-synthesized generative adversarial networks for image-to-image transformation[J]. arXiv preprint arXiv: 1901.03554, 2019.
[43] [43] ZHENG J, SONG W, WU Y, et al.. Feature encoder guided generative adversarial network for face photo-sketch synthesis[J]. IEEE Access, 2019, 7(1): 154971-154985.
ZHENG J, SONG W, WU Y, et al.. Feature encoder guided generative adversarial network for face photo-sketch synthesis[J]. IEEE Access, 2019, 7(1): 154971-154985.
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MING Yue, WANG Shao-Ying, FAN Chun-Xiao, ZHOU Jiang-Wan. Exploring aligned latent representations for cross-domain face recognition[J]. Optics and Precision Engineering, 2020, 28(10): 2311
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Received: Jul. 9, 2020
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Published Online: Nov. 25, 2020
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