{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T18:25:18Z","timestamp":1776882318694,"version":"3.51.2"},"reference-count":138,"publisher":"Springer Science and Business Media LLC","issue":"8-9","license":[{"start":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T00:00:00Z","timestamp":1585008000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T00:00:00Z","timestamp":1585008000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"State Key Development Program","award":["2016YFB1001001"],"award-info":[{"award-number":["2016YFB1001001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1736119"],"award-info":[{"award-number":["U1736119"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["DUT18JC06"],"award-info":[{"award-number":["DUT18JC06"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s11263-020-01308-z","type":"journal-article","created":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T09:03:46Z","timestamp":1585040626000},"page":"2002-2034","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["A Survey of Deep Facial Attribute Analysis"],"prefix":"10.1007","volume":"128","author":[{"given":"Xin","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Yanqing","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Huaibo","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ran","family":"He","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,24]]},"reference":[{"key":"1308_CR1","unstructured":"Belghazi, M. I., Rajeswar, S., Mastropietro, O., Rostamzadeh, N., Mitrovic, J., & Courville, A. (2018). Hierarchical adversarially learned inference. arXiv preprint arXiv:1802.01071."},{"key":"1308_CR2","unstructured":"Berg, T., & Belhumeur, P. N. (2013). Poof: Part-based one-vs.-one features for fine-grained categorization, face verification, and attribute estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 955\u2013962). IEEE."},{"key":"1308_CR3","unstructured":"Berthelot, D., Raffel, C., Roy, A., & Goodfellow, I. (2019). Understanding and improving interpolation in autoencoders via an adversarial regularizer. In Proceedings of the international conference on learning representations (ICLR)."},{"key":"1308_CR4","doi-asserted-by":"crossref","unstructured":"Bourdev, L., Maji, S., & Malik, J. (2011). Describing people: A poselet-based approach to attribute classification. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 1543\u20131550). IEEE.","DOI":"10.1109\/ICCV.2011.6126413"},{"key":"1308_CR5","doi-asserted-by":"crossref","unstructured":"Bourdev, L., & Malik, J. (2009). Poselets: Body part detectors trained using 3d human pose annotations. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 1365\u20131372). IEEE.","DOI":"10.1109\/ICCV.2009.5459303"},{"key":"1308_CR6","doi-asserted-by":"publisher","first-page":"2750","DOI":"10.1109\/TMM.2019.2911457","volume":"21","author":"C Cao","year":"2019","unstructured":"Cao, C., Lu, F., Li, C., Lin, S., & Shen, X. (2019a). Makeup removal via bidirectional tunable de-makeup network. IEEE Transactions on Multimedia, 21, 2750\u20132761.","journal-title":"IEEE Transactions on Multimedia"},{"issue":"8","key":"1308_CR7","doi-asserted-by":"publisher","first-page":"2028","DOI":"10.1109\/TIFS.2019.2891116","volume":"14","author":"J Cao","year":"2019","unstructured":"Cao, J., Hu, Y., Yu, B., He, R., & Sun, Z. (2019b). 3D aided duet gans for multi-view face image synthesis. IEEE Transactions on Information Forensics and Security (TIFS), 14(8), 2028\u20132042.","journal-title":"IEEE Transactions on Information Forensics and Security (TIFS)"},{"key":"1308_CR8","doi-asserted-by":"crossref","unstructured":"Cao, J., Li, Y., & Zhang, Z. (2018). Partially shared multi-task convolutional neural network with local constraint for face attribute learning. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 4290\u20134299).","DOI":"10.1109\/CVPR.2018.00451"},{"key":"1308_CR9","doi-asserted-by":"crossref","unstructured":"Chang, H., Lu, J., Yu, F., & Finkelstein, A. (2018). Pairedcyclegan: Asymmetric style transfer for applying and removing makeup. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 40\u201348).","DOI":"10.1109\/CVPR.2018.00012"},{"issue":"2\u20134","key":"1308_CR10","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1007\/s11263-017-1029-3","volume":"126","author":"JC Chen","year":"2018","unstructured":"Chen, J. C., Ranjan, R., Sankaranarayanan, S., Kumar, A., Chen, C. H., Patel, V. M., et al. (2018). Unconstrained still\/video-based face verification with deep convolutional neural networks. International Journal of Computer Vision (IJCV), 126(2\u20134), 272\u2013291.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1308_CR11","doi-asserted-by":"crossref","unstructured":"Chen, L., Zhang, Q., & Li, B. (2014). Predicting multiple attributes via relative multi-task learning. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1027\u20131034).","DOI":"10.1109\/CVPR.2014.135"},{"key":"1308_CR12","unstructured":"Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., & Abbeel, P. (2016). Infogan: Interpretable representation learning by information maximizing generative adversarial nets. In Advances in neural information processing systems (NIPS) (pp. 2172\u20132180)."},{"key":"1308_CR13","doi-asserted-by":"crossref","unstructured":"Chen, Y. C., Shen, X., Lin, Z., Lu, X., Pao, I., Jia, J., et\u00a0al. (2019). Semantic component decomposition for face attribute manipulation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 9859\u20139867).","DOI":"10.1109\/CVPR.2019.01009"},{"key":"1308_CR14","doi-asserted-by":"crossref","unstructured":"Chhabra, S., Singh, R., Vatsa, M., & Gupta, G. (2018) Anonymizing k-facial attributes via adversarial perturbations. In Proceedings of the international joint conference on artificial intelligence (IJCAI) (pp. 656\u2013662).","DOI":"10.24963\/ijcai.2018\/91"},{"key":"1308_CR15","doi-asserted-by":"crossref","unstructured":"Choi, Y., Choi, M., & Kim, M. (2018). Stargan: Unified generative adversarial networks for multi-domain image-to-image translation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 8789\u20138797).","DOI":"10.1109\/CVPR.2018.00916"},{"issue":"3","key":"1308_CR16","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273\u2013297.","journal-title":"Machine Learning"},{"key":"1308_CR17","doi-asserted-by":"crossref","unstructured":"Ding, H., Zhou, H., Zhou, S. K., & Chellappa, R. (2018). A deep cascade network for unaligned face attribute classification. In Proceedings of the conference on artificial intelligence (AAAI).","DOI":"10.1609\/aaai.v32i1.12303"},{"key":"1308_CR18","doi-asserted-by":"crossref","unstructured":"Dong, Q., Gong, S., & Zhu, X. (2017). Class rectification hard mining for imbalanced deep learning. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 1869\u20131878). IEEE.","DOI":"10.1109\/ICCV.2017.205"},{"key":"1308_CR19","unstructured":"Dorta, G., Vicente, S., Campbell, N. D., & Simpson, I. (2018). The GAN that warped: Semantic attribute editing with unpaired data. arXiv preprint arXiv:1811.12784."},{"key":"1308_CR20","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1007\/s11263-018-1064-8","volume":"126","author":"B Egger","year":"2018","unstructured":"Egger, B., Sch\u00f6nborn, S., Schneider, A., Kortylewski, A., Morel-Forster, A., Blumer, C., et al. (2018). Occlusion-aware 3d morphable models and an illumination prior for face image analysis. International Journal of Computer Vision (IJCV), 126, 1269\u20131287.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1308_CR21","doi-asserted-by":"crossref","unstructured":"Fan, Q., Gabbur, P., & Pankanti, S. (2013). Relative attributes for large-scale abandoned object detection. In Proceedings of the IEEE International conference on computer vision (ICCV) (pp. 2736\u20132743).","DOI":"10.1109\/ICCV.2013.340"},{"issue":"1","key":"1308_CR22","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1186\/s13640-018-0282-x","volume":"2018","author":"Y Fang","year":"2018","unstructured":"Fang, Y., & Yuan, Q. (2018). Attribute-enhanced metric learning for face retrieval. EURASIP Journal on Image and Video Processing, 2018(1), 44.","journal-title":"EURASIP Journal on Image and Video Processing"},{"key":"1308_CR23","doi-asserted-by":"crossref","unstructured":"Fathy, M. E., Patel, V. M., & Chellappa, R. (2015). Face-based active authentication on mobile devices. In Proceedings of the IEEE conference on acoustics, speech and signal processing (ICASSP) (pp. 1687\u20131691). IEEE.","DOI":"10.1109\/ICASSP.2015.7178258"},{"key":"1308_CR24","doi-asserted-by":"crossref","unstructured":"Fukui, H., Hirakawa, T., Yamashita, T., & Fujiyoshi, H. (2019). Attention branch network: Learning of attention mechanism for visual explanation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 10705\u201310714).","DOI":"10.1109\/CVPR.2019.01096"},{"key":"1308_CR25","doi-asserted-by":"crossref","unstructured":"Gkioxari, G., Girshick, R., & Malik, J. (2015). Actions and attributes from wholes and parts. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 2470\u20132478). IEEE.","DOI":"10.1109\/ICCV.2015.284"},{"issue":"5","key":"1308_CR26","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/s11263-017-1048-0","volume":"126","author":"A Gonzalez-Garcia","year":"2018","unstructured":"Gonzalez-Garcia, A., Modolo, D., & Ferrari, V. (2018). Do semantic parts emerge in convolutional neural networks? International Journal of Computer Vision (IJCV), 126(5), 476\u2013494.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1308_CR27","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., et\u00a0al. (2014). Generative adversarial nets. In Advances in neural information processing systems (NIPS) (pp. 2672\u20132680)."},{"key":"1308_CR28","unstructured":"Goodfellow, I. J., Shlens, J., & Szegedy, C. (2015). Explaining and harnessing adversarial examples. In Proceedings of the international conference on learning representations (ICLR)."},{"key":"1308_CR29","doi-asserted-by":"crossref","unstructured":"G\u00fcnther, M., Costa-Pazo, A., Ding, C., Boutellaa, E., Chiachia, G., Zhang, H., et\u00a0al. (2013). The 2013 face recognition evaluation in mobile environment. In Proceedings of the international conference on biometrics (ICB) (pp. 1\u20137). IEEE.","DOI":"10.1109\/ICB.2013.6613024"},{"key":"1308_CR30","doi-asserted-by":"crossref","unstructured":"G\u00fcnther, M., Rozsa, A., & Boult, T. E. (2017). AFFACT: Alignment-free facial attribute classification technique. In Proceedings of the IEEE international joint conference on biometrics (IJCB) (pp. 90\u201399). IEEE.","DOI":"10.1109\/BTAS.2017.8272686"},{"key":"1308_CR31","doi-asserted-by":"crossref","unstructured":"Hadid, A., Heikkila, J., Silv\u00e9n, O., & Pietikainen, M. (2007). Face and eye detection for person authentication in mobile phones. In Proceedings of the ACM\/IEEE international conference on distributed smart cameras (pp. 101\u2013108). IEEE.","DOI":"10.1109\/ICDSC.2007.4357512"},{"key":"1308_CR32","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.eswa.2016.12.035","volume":"73","author":"G Haixiang","year":"2017","unstructured":"Haixiang, G., Yijing, L., Shang, J., Mingyun, G., Yuanyue, H., & Bing, G. (2017). Learning from class-imbalanced data: Review of methods and applications. Expert Systems with Applications, 73, 220\u2013239.","journal-title":"Expert Systems with Applications"},{"key":"1308_CR33","doi-asserted-by":"publisher","first-page":"2597","DOI":"10.1109\/TPAMI.2017.2738004","volume":"40","author":"H Han","year":"2017","unstructured":"Han, H., Jain, A. K., Shan, S., & Chen, X. (2017). Heterogeneous face attribute estimation: A deep multi-task learning approach. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 40, 2597\u20132609.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1308_CR34","doi-asserted-by":"crossref","unstructured":"Hand, E. M., Castillo, C. D., & Chellappa, R. (2018a). Doing the best we can with what we have: Multi-label balancing with selective learning for attribute prediction. In Proceedings of the conference on artificial intelligence (AAAI) (pp. 6878\u20136885).","DOI":"10.1609\/aaai.v32i1.12313"},{"key":"1308_CR35","doi-asserted-by":"crossref","unstructured":"Hand, E. M., Castillo, C. D., & Chellappa, R. (2018b). Predicting facial attributes in video using temporal coherence and motion-attention. In Proceedings of the IEEE winter conference on applications of computer vision (WACV) (pp. 84\u201392). IEEE.","DOI":"10.1109\/WACV.2018.00017"},{"key":"1308_CR36","doi-asserted-by":"crossref","unstructured":"Hand, E. M., & Chellappa, R. (2017). Attributes for improved attributes: A multi-task network utilizing implicit and explicit relationships for facial attribute classification. In Proceedings of the conference on artificial intelligence (AAAI) (pp. 4068\u20134074).","DOI":"10.1609\/aaai.v31i1.11229"},{"key":"1308_CR37","unstructured":"He, D., Xia, Y., Qin, T., Wang, L., Yu, N., Liu, T., & Ma, W. Y. (2016a). Dual learning for machine translation. In Advances in neural information processing systems (NIPS) (pp. 820\u2013828)."},{"key":"1308_CR38","unstructured":"He, K., Fu, Y., & Xue, X. (2017). A jointly learned deep architecture for facial attribute analysis and face detection in the wild. arXiv preprint arXiv:1707.08705."},{"key":"1308_CR39","doi-asserted-by":"crossref","unstructured":"He, K., Fu, Y., Zhang, W., Wang, C., Jiang, Y. G., Huang, F., & Xue, X. (2018a). Harnessing synthesized abstraction images to improve facial attribute recognition. In Proceedings of the international joint conference on artificial intelligence (IJCAI).","DOI":"10.24963\/ijcai.2018\/102"},{"key":"1308_CR40","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2016b). Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 770\u2013778).","DOI":"10.1109\/CVPR.2016.90"},{"key":"1308_CR41","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.patcog.2017.02.005","volume":"75","author":"R He","year":"2018","unstructured":"He, R., Tan, T., Davis, L., & Sun, Z. (2018b). Learning structured ordinal measures for video based face recognition. Pattern Recognition, 75, 4\u201314.","journal-title":"Pattern Recognition"},{"key":"1308_CR42","doi-asserted-by":"publisher","first-page":"1761","DOI":"10.1109\/TPAMI.2018.2842770","volume":"41","author":"R He","year":"2018","unstructured":"He, R., Wu, X., Sun, Z., & Tan, T. (2018c). Wasserstein CNN: Learning invariant features for NIR-VIS face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41, 1761\u20131773.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1308_CR43","doi-asserted-by":"publisher","first-page":"5464","DOI":"10.1109\/TIP.2019.2916751","volume":"28","author":"Z He","year":"2019","unstructured":"He, Z., Zuo, W., Kan, M., Shan, S., & Chen, X. (2019). Attgan: Facial attribute editing by only changing what you want. IEEE Transactions on Image Processing (TIP), 28, 5464\u20135478.","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"1308_CR44","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., & Hochreiter, S. (2017). Gans trained by a two time-scale update rule converge to a local nash equilibrium. In Advances in neural information processing systems (NIPS) (pp. 6626\u20136637)."},{"key":"1308_CR45","doi-asserted-by":"crossref","unstructured":"Hu, Y., Wu, X., Yu, B., He, R., & Sun, Z. (2018). Pose-guided photorealistic face rotation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR).","DOI":"10.1109\/CVPR.2018.00876"},{"key":"1308_CR46","doi-asserted-by":"crossref","unstructured":"Huang, C., Li, Y., Change\u00a0Loy, C., & Tang, X. (2016). Learning deep representation for imbalanced classification. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 5375\u20135384).","DOI":"10.1109\/CVPR.2016.580"},{"key":"1308_CR47","doi-asserted-by":"publisher","unstructured":"Huang, C., Li, Y., Chen, C. L., & Tang, X. (2019). Deep imbalanced learning for face recognition and attribute prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). https:\/\/doi.org\/10.1109\/TPAMI.2019.2914680.","DOI":"10.1109\/TPAMI.2019.2914680"},{"key":"1308_CR48","unstructured":"Huang, G. B., Mattar, M., Berg, T., & Learned-Miller, E. (2008). Labeled faces in the wild: A database forstudying face recognition in unconstrained environments. In Workshop on faces in \u2018Real-Life\u2019 images: Detection, alignment, and recognition."},{"key":"1308_CR49","unstructured":"Huang, H., He, R., Sun, Z., Tan, T., et\u00a0al. (2018a). Introvae: Introspective variational autoencoders for photographic image synthesis. In Advances in neural information processing systems (NIPS) (pp. 52\u201363)."},{"key":"1308_CR50","unstructured":"Huang, H., Song, L., He, R., Sun, Z., & Tan, T. (2018b). Variational capsules for image analysis and synthesis. arXiv preprint arXiv:1807.04099."},{"key":"1308_CR51","doi-asserted-by":"crossref","unstructured":"Kalayeh, M. M., Gong, B., & Shah, M. (2017). Improving facial attribute prediction using semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 4227\u20134235). IEEE.","DOI":"10.1109\/CVPR.2017.450"},{"key":"1308_CR52","doi-asserted-by":"crossref","unstructured":"Kazemi, V., & Sullivan, J. (2014). One millisecond face alignment with an ensemble of regression trees. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1867\u20131874).","DOI":"10.1109\/CVPR.2014.241"},{"key":"1308_CR53","unstructured":"Kingma, D. P., & Welling, M. (2013). Auto-encoding variational bayes. In Proceedings of the international conference on learning representations (ICLR)."},{"key":"1308_CR54","doi-asserted-by":"crossref","unstructured":"Kumar, N., Belhumeur, P., & Nayar, S. (2008). Facetracer: A search engine for large collections of images with faces. In Proceedings of the European conference on computer vision (ECCV) (pp. 340\u2013353). Springer.","DOI":"10.1007\/978-3-540-88693-8_25"},{"issue":"10","key":"1308_CR55","doi-asserted-by":"publisher","first-page":"1962","DOI":"10.1109\/TPAMI.2011.48","volume":"33","author":"N Kumar","year":"2011","unstructured":"Kumar, N., Berg, A., Belhumeur, P. N., & Nayar, S. (2011). Describable visual attributes for face verification and image search. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 33(10), 1962\u20131977.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1308_CR56","doi-asserted-by":"crossref","unstructured":"Kumar, N., Berg, A. C., Belhumeur, P. N., & Nayar, S. K. (2009). Attribute and simile classifiers for face verification. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 365\u2013372). IEEE.","DOI":"10.1109\/ICCV.2009.5459250"},{"key":"1308_CR57","doi-asserted-by":"crossref","unstructured":"Lampert, C. H., Nickisch, H., & Harmeling, S. (2009). Learning to detect unseen object classes by between-class attribute transfer. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 951\u2013958). IEEE.","DOI":"10.1109\/CVPR.2009.5206594"},{"key":"1308_CR58","unstructured":"Lample, G., Zeghidour, N., Usunier, N., Bordes, A., Denoyer, L., et\u00a0al. (2017). Fader networks: Manipulating images by sliding attributes. In Advances in neural information processing systems (NIPS) (pp. 5967\u20135976)."},{"key":"1308_CR59","unstructured":"Larsen, A. B. L., S\u00f8nderby, S. K., Larochelle, H., & Winther, O. (2016). Autoencoding beyond pixels using a learned similarity metric. In Proceedings of the IEEE international conference on machine learning (ICML) (pp. 1558\u20131566)."},{"key":"1308_CR60","doi-asserted-by":"crossref","unstructured":"Le, V., Brandt, J., Lin, Z., Bourdev, L., & Huang, T. S. (2012). Interactive facial feature localization. In Proceedings of the European conference on computer vision (ECCV) (pp. 679\u2013692). Springer.","DOI":"10.1007\/978-3-642-33712-3_49"},{"issue":"3","key":"1308_CR61","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1007\/s11390-018-1835-2","volume":"33","author":"HY Li","year":"2018","unstructured":"Li, H. Y., Dong, W. M., & Hu, B. G. (2018a). Facial image attributes transformation via conditional recycle generative adversarial networks. Journal of Computer Science and Technology (JCST), 33(3), 511\u2013521.","journal-title":"Journal of Computer Science and Technology (JCST)"},{"issue":"9","key":"1308_CR62","doi-asserted-by":"publisher","first-page":"4651","DOI":"10.1109\/TIP.2018.2839521","volume":"27","author":"J Li","year":"2018","unstructured":"Li, J., Zhao, F., Feng, J., Roy, S., Yan, S., & Sim, T. (2018b). Landmark free face attribute prediction. IEEE Transactions on Image Processing (TIP), 27(9), 4651\u20134662.","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"1308_CR63","unstructured":"Li, M., Zuo, W., & Zhang, D. (2016). Deep identity-aware transfer of facial attributes. arXiv preprint arXiv:1610.05586."},{"key":"1308_CR64","doi-asserted-by":"crossref","unstructured":"Li, T., Qian, R., Dong, C., Liu, S., Yan, Q., Zhu, W., & Lin, L. (2018c). Beautygan: Instance-level facial makeup transfer with deep generative adversarial network. In Proceedings of the ACM multimedia conference on multimedia conference (ACMMM) (pp. 645\u2013653). ACM.","DOI":"10.1145\/3240508.3240618"},{"key":"1308_CR65","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, R., Liu, H., Jiang, H., Shan, S., & Chen, X. (2015). Two birds, one stone: Jointly learning binary code for large-scale face image retrieval and attributes prediction. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 3819\u20133827). IEEE.","DOI":"10.1109\/ICCV.2015.435"},{"key":"1308_CR66","unstructured":"Liu, A. H., Liu, Y. C., Yeh, Y. Y., & Wang, Y. C. F. (2018). A unified feature disentangler for multi-domain image translation and manipulation. In Advances in neural information processing systems (NIPS) (pp. 2591\u20132600)."},{"key":"1308_CR67","doi-asserted-by":"crossref","unstructured":"Liu, M. Y., Breuel, T., & Kautz, J. (2017). Unsupervised image-to-image translation networks. In Advances in neural information processing systems (NIPS) (pp. 700\u2013708).","DOI":"10.1007\/978-3-319-70139-4"},{"key":"1308_CR68","doi-asserted-by":"crossref","unstructured":"Liu, Y., Li, Q., & Sun, Z. (2019). Attribute-aware face aging with wavelet-based generative adversarial networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 11877\u201311886).","DOI":"10.1109\/CVPR.2019.01215"},{"key":"1308_CR69","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., & Tang, X. (2015). Deep learning face attributes in the wild. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 3730\u20133738).","DOI":"10.1109\/ICCV.2015.425"},{"key":"1308_CR70","doi-asserted-by":"crossref","unstructured":"Lu, Y., Kumar, A., Zhai, S., Cheng, Y., Javidi, T., & Feris, R. (2017). Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (Vol.\u00a01, p.\u00a06).","DOI":"10.1109\/CVPR.2017.126"},{"key":"1308_CR71","doi-asserted-by":"crossref","unstructured":"Lu, Y., Tai, Y. W., & Tang, C. K. (2018a) Attribute-guided face generation using conditional cyclegan. In Proceedings of the European conference on computer vision (ECCV) (pp. 293\u2013308). Springer.","DOI":"10.1007\/978-3-030-01258-8_18"},{"key":"1308_CR72","doi-asserted-by":"crossref","unstructured":"Lu, Z., Hu, T., Song, L., Zhang, Z., & He, R. (2018b). Conditional expression synthesis with face parsing transformation. In Proceedings of the ACM international conference on multimedia (ACMMM) (pp. 1083\u20131091). ACM.","DOI":"10.1145\/3240508.3240647"},{"key":"1308_CR73","doi-asserted-by":"crossref","unstructured":"Luo, P., Wang, X., & Tang, X. (2013). A deep sum-product architecture for robust facial attributes analysis. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 2864\u20132871). IEEE.","DOI":"10.1109\/ICCV.2013.356"},{"key":"1308_CR74","unstructured":"Ma, L., Jia, X., Georgoulis, S., Tuytelaars, T., & Van\u00a0Gool, L. (2018). Exemplar guided unsupervised image-to-image translation with semantic consistency. In Proceedings of the international conference on learning representations (ICLR)."},{"key":"1308_CR75","doi-asserted-by":"publisher","unstructured":"Mahbub, U., Sarkar, S., & Chellappa, R. (2018). Segment-based methods for facial attribute detection from partial faces. IEEE Transactions on Affective Computing. https:\/\/doi.org\/10.1109\/TAFFC.2018.2820048.","DOI":"10.1109\/TAFFC.2018.2820048"},{"key":"1308_CR76","doi-asserted-by":"crossref","unstructured":"Meng, Z., Adluru, N., Kim, H. J., Fung, G., & Singh, V. (2018). Efficient relative attribute learning using graph neural networks. In Proceedings of the European conference on computer vision (ECCV) (pp. 552\u2013567).","DOI":"10.1007\/978-3-030-01264-9_34"},{"key":"1308_CR77","unstructured":"Miller, T. L., Berg, A. C., Edwards, J. A., Maire, M. R., White, R. M., Teh, Y. W., et\u00a0al. (2007). Names and faces."},{"key":"1308_CR78","unstructured":"Mirza, M., & Osindero, S. (2014). Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784."},{"key":"1308_CR79","doi-asserted-by":"crossref","unstructured":"Nguyen, H. M., Ly, N. Q., & Phung, T. T. (2018). Large-scale face image retrieval system at attribute level based on facial attribute ontology and deep neuron network. In Asian conference on intelligent information and database systems (pp. 539\u2013549). Springer.","DOI":"10.1007\/978-3-319-75420-8_51"},{"key":"1308_CR80","unstructured":"Nhan\u00a0Duong, C., Luu, K., Gia\u00a0Quach, K., Nguyen, N., Patterson, E., Bui, T. D., Le, N. (2019). Automatic face aging in videos via deep reinforcement learning. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 10013\u201310022)."},{"key":"1308_CR81","doi-asserted-by":"crossref","unstructured":"Parikh, D., & Grauman, K. (2011). Relative attributes. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 503\u2013510). IEEE.","DOI":"10.1109\/ICCV.2011.6126281"},{"key":"1308_CR82","doi-asserted-by":"crossref","unstructured":"Parkhi, O. M., Vedaldi, A., Zisserman, A., et\u00a0al. (2015). Deep face recognition. In Proceedings of the British machine vision conference 2015, (BMVC) (Vol.\u00a01, p.\u00a06).","DOI":"10.5244\/C.29.41"},{"key":"1308_CR83","unstructured":"Perarnau, G., van\u00a0de Weijer, J., Raducanu, B., & \u00c1lvarez, J. M. (2016). Invertible conditional gans for image editing. In Advances in neural information processing systems workshop on adversarial training (NIPSW)."},{"key":"1308_CR84","doi-asserted-by":"crossref","unstructured":"Philbin, J., Chum, O., Isard, M., Sivic, J., & Zisserman, A. (2007). Object retrieval with large vocabularies and fast spatial matching. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1\u20138). IEEE.","DOI":"10.1109\/CVPR.2007.383172"},{"key":"1308_CR85","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1109\/TPAMI.2017.2781233","volume":"41","author":"R Ranjan","year":"2017","unstructured":"Ranjan, R., Patel, V. M., & Chellappa, R. (2017). Hyperface: A deep multi-task learning framework for face detection, landmark localization, pose estimation, and gender recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41, 121\u2013135.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1308_CR86","doi-asserted-by":"crossref","unstructured":"Ranjan, R., Sankaranarayanan, S., Castillo, C. D., & Chellappa, R. (2017). An all-in-one convolutional neural network for face analysis. In Proceedings of the IEEE international conference on automatic face & gesture recognition (FG) (pp. 17\u201324). IEEE.","DOI":"10.1109\/FG.2017.137"},{"key":"1308_CR87","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1007\/s11263-018-1135-x","volume":"127","author":"Y Rao","year":"2018","unstructured":"Rao, Y., Lu, J., & Zhou, J. (2018). Learning discriminative aggregation network for video-based face recognition and person re-identification. International Journal of Computer Vision (IJCV), 127, 701\u2013718.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1308_CR88","unstructured":"Rozsa, A., G\u00fcnther, M., Rudd, E. M., & Boult, T. E. (2016). Are facial attributes adversarially robust? In Processing of international conference on pattern recognition (ICPR) (pp. 3121\u20133127). IEEE."},{"key":"1308_CR89","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.patrec.2017.10.024","volume":"124","author":"A Rozsa","year":"2017","unstructured":"Rozsa, A., G\u00fcnther, M., Rudd, E. M., & Boult, T. E. (2017). Facial attributes: Accuracy and adversarial robustness. Pattern Recognition Letters, 124, 100\u2013108.","journal-title":"Pattern Recognition Letters"},{"key":"1308_CR90","doi-asserted-by":"crossref","unstructured":"Rudd, E. M., G\u00fcnther, M., & Boult, T. E. (2016). Moon: A mixed objective optimization network for the recognition of facial attributes. In Proceedings of the European conference on computer vision (ECCV) (pp. 19\u201335). Springer.","DOI":"10.1007\/978-3-319-46454-1_2"},{"key":"1308_CR91","doi-asserted-by":"crossref","unstructured":"Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., & Pantic, M. (2013). A semi-automatic methodology for facial landmark annotation. In Proceedings of the IEEE conference on computer vision and pattern recognition workshops (CVPRW) (pp. 896\u2013903).","DOI":"10.1109\/CVPRW.2013.132"},{"key":"1308_CR92","doi-asserted-by":"crossref","unstructured":"Saito, M., Matsumoto, E., & Saito, S. (2017). Temporal generative adversarial nets with singular value clipping. In Proceedings of the IEEE international conference on computer vision (pp. 2830\u20132839).","DOI":"10.1109\/ICCV.2017.308"},{"key":"1308_CR93","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.imavis.2016.05.004","volume":"58","author":"P Samangouei","year":"2017","unstructured":"Samangouei, P., Patel, V. M., & Chellappa, R. (2017). Facial attributes for active authentication on mobile devices. Image and Vision Computing, 58, 181\u2013192.","journal-title":"Image and Vision Computing"},{"key":"1308_CR94","doi-asserted-by":"crossref","unstructured":"Sandeep, R. N., Verma, Y., & Jawahar, C. (2014). Relative parts: Distinctive parts for learning relative attributes. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 3614\u20133621).","DOI":"10.1109\/CVPR.2014.462"},{"key":"1308_CR95","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., & Philbin, J. (2015). Facenet: A unified embedding for face recognition and clustering. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 815\u2013823).","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"1308_CR96","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.patrec.2018.03.010","volume":"119","author":"A Sethi","year":"2018","unstructured":"Sethi, A., Singh, M., Singh, R., & Vatsa, M. (2018). Residual codean autoencoder for facial attribute analysis. Pattern Recognition Letters, 119, 157\u2013165.","journal-title":"Pattern Recognition Letters"},{"key":"1308_CR97","doi-asserted-by":"crossref","unstructured":"Shen, W., & Liu, R. (2017). Learning residual images for face attribute manipulation. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1225\u20131233). IEEE.","DOI":"10.1109\/CVPR.2017.135"},{"key":"1308_CR98","doi-asserted-by":"publisher","unstructured":"Shi, H., & Tao, L. (2018). Fine-grained visual comparison based on relative attribute quadratic discriminant analysis. IEEE Transactions on Systems, Man, and Cybernetics: Systems. https:\/\/doi.org\/10.1109\/TSMC.2018.2800092.","DOI":"10.1109\/TSMC.2018.2800092"},{"key":"1308_CR99","doi-asserted-by":"crossref","unstructured":"Shi, Z., Hospedales, T. M., & Xiang, T. (2015). Transferring a semantic representation for person re-identification and search. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 4184\u20134193). IEEE.","DOI":"10.1109\/CVPR.2015.7299046"},{"key":"1308_CR100","doi-asserted-by":"crossref","unstructured":"Singh, K. K., & Lee, Y. J. (2016). End-to-end localization and ranking for relative attributes. In Proceedings of the European conference on computer vision (ECCV) (pp. 753\u2013769). Springer.","DOI":"10.1007\/978-3-319-46466-4_45"},{"key":"1308_CR101","doi-asserted-by":"crossref","unstructured":"Smith, B. M., Zhang, L., Brandt, J., Lin, Z., & Yang, J. (2013). Exemplar-based face parsing. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 3484\u20133491). IEEE.","DOI":"10.1109\/CVPR.2013.447"},{"key":"1308_CR102","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/j.cviu.2014.02.010","volume":"122","author":"F Song","year":"2014","unstructured":"Song, F., Tan, X., & Chen, S. (2014). Exploiting relationship between attributes for improved face verification. Computer Vision and Image Understanding, 122, 143\u2013154.","journal-title":"Computer Vision and Image Understanding"},{"key":"1308_CR103","doi-asserted-by":"crossref","unstructured":"Song, L., Cao, J., Song, L., Hu, Y., & He, R. (2019). Geometry-aware face completion and editing. In Proceedings of the conference on artificial intelligence (AAAI).","DOI":"10.1609\/aaai.v33i01.33012506"},{"key":"1308_CR104","doi-asserted-by":"crossref","unstructured":"Song, L., Lu, Z., He, R., Sun, Z., Tan, T. (2018a). Geometry guided adversarial facial expression synthesis. In Proceedings of the ACM international conference on multimedia (ACMMM) (pp. 627\u2013635). ACM.","DOI":"10.1145\/3240508.3240612"},{"key":"1308_CR105","doi-asserted-by":"crossref","unstructured":"Song, L., Zhang, M., Wu, X., & He, R. (2018b). Adversarial discriminative heterogeneous face recognition. In Proceedings of the conference on artificial intelligence (AAAI).","DOI":"10.1609\/aaai.v32i1.12291"},{"key":"1308_CR106","unstructured":"Sun, R., Huang, C., Shi, J., & Ma, L. (2018c). Mask-aware photorealistic face attribute manipulation. arXiv preprint arXiv:1804.08882."},{"key":"1308_CR107","unstructured":"Sun, Y., Chen, Y., Wang, X., & Tang, X. (2014). Deep learning face representation by joint identification-verification. In Advances in neural information processing systems (NIPS) (pp. 1988\u20131996)."},{"issue":"3","key":"1308_CR108","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1109\/TPAMI.2009.39","volume":"32","author":"J Suo","year":"2010","unstructured":"Suo, J., Zhu, S. C., Shan, S., & Chen, X. (2010). A compositional and dynamic model for face aging. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 32(3), 385\u2013401.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)"},{"key":"1308_CR109","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. A. (2017). Inception-v4, inception-resnet and the impact of residual connections on learning. In Proceedings of the conference on artificial intelligence (AAAI) (Vol.\u00a04, p.\u00a012).","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"1308_CR110","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2014). Intriguing properties of neural networks. In Proceedings of the international conference on learning representations (ICLR)."},{"key":"1308_CR111","doi-asserted-by":"crossref","unstructured":"Taherkhani, F., Nasrabadi, N. M., & Dawson, J. (2018). A deep face identification network enhanced by facial attributes prediction. In Proceedings of the IEEE conference on computer vision and pattern recognition workshops (CVPRW) (pp. 553\u2013560).","DOI":"10.1109\/CVPRW.2018.00097"},{"key":"1308_CR112","doi-asserted-by":"crossref","unstructured":"Toderici, G., O\u2019malley, S.M., Passalis, G., Theoharis, T., Kakadiaris, I.A.: Ethnicity-and gender-based subject retrieval using 3-d face-recognition techniques. International Journal of Computer Vision (IJCV) 89(2-3), 382\u2013391 (2010).","DOI":"10.1007\/s11263-009-0300-7"},{"issue":"6","key":"1308_CR113","doi-asserted-by":"publisher","first-page":"1501","DOI":"10.1109\/TIFS.2018.2881671","volume":"14","author":"M Trokielewicz","year":"2019","unstructured":"Trokielewicz, M., Czajka, A., & Maciejewicz, P. (2019). Iris recognition after death. IEEE Transactions on Information Forensics and Security, 14(6), 1501\u20131514.","journal-title":"IEEE Transactions on Information Forensics and Security"},{"issue":"3","key":"1308_CR114","first-page":"572","volume":"86","author":"JA Tropp","year":"2006","unstructured":"Tropp, J. A., Gilbert, A. C., & Strauss, M. J. (2006). Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit. Signal Processing, 86(3), 572\u2013588.","journal-title":"Part I: Greedy pursuit. Signal Processing"},{"key":"1308_CR115","doi-asserted-by":"crossref","unstructured":"Wang, J., Cheng, Y., & Schmidt\u00a0Feris, R. (2016). Walk and learn: Facial attribute representation learning from egocentric video and contextual data. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 2295\u20132304).","DOI":"10.1109\/CVPR.2016.252"},{"key":"1308_CR116","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, S., Qi, G., Tang, J., & Li, B. (2018). Weakly supervised facial attribute manipulation via deep adversarial network. In Proceedings of the IEEE winter conference on applications of computer vision (WACV) (pp. 112\u2013121). IEEE.","DOI":"10.1109\/WACV.2018.00019"},{"issue":"4","key":"1308_CR117","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing (TIP), 13(4), 600\u2013612.","journal-title":"IEEE Transactions on Image Processing (TIP)"},{"key":"1308_CR118","unstructured":"Wiles, O., Koepke, A., & Zisserman, A. (2018). Self-supervised learning of a facial attribute embedding from video. In Proceedings of the British machine vision conference (BMVC) (p. 302)."},{"key":"1308_CR119","doi-asserted-by":"crossref","unstructured":"Wolf, L., Hassner, T., & Maoz, I. (2011). Face recognition in unconstrained videos with matched background similarity. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 529\u2013534). IEEE Computer Society.","DOI":"10.1109\/CVPR.2011.5995566"},{"key":"1308_CR120","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s11263-018-1097-z","volume":"127","author":"Y Wu","year":"2017","unstructured":"Wu, Y., & Ji, Q. (2017). Facial landmark detection: A literature survey. International Journal of Computer Vision (IJCV), 127, 115\u2013142.","journal-title":"International Journal of Computer Vision (IJCV)"},{"key":"1308_CR121","doi-asserted-by":"crossref","unstructured":"Xiao, F., & Jae\u00a0Lee, Y. (2015) Discovering the spatial extent of relative attributes. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 1458\u20131466).","DOI":"10.1109\/ICCV.2015.171"},{"key":"1308_CR122","unstructured":"Xiao, T., Hong, J., & Ma, J. (2017). DNA-GAN: Learning disentangled representations from multi-attribute images. In Proceedings of the international conference on learning representations workshop track (ICLRW)."},{"key":"1308_CR123","doi-asserted-by":"crossref","unstructured":"Xiao, T., Hong, J., & Ma, J. (2018). Elegant: Exchanging latent encodings with gan for transferring multiple face attributes. In Proceedings of the European conference on computer vision (ECCV) (pp. 168\u2013184).","DOI":"10.1007\/978-3-030-01249-6_11"},{"key":"1308_CR124","doi-asserted-by":"crossref","unstructured":"Yan, X., Yang, J., Sohn, K., & Lee, H. (2016). Attribute2image: Conditional image generation from visual attributes. In Proceedings of the European conference on computer vision (ECCV) (pp. 776\u2013791). Springer.","DOI":"10.1007\/978-3-319-46493-0_47"},{"key":"1308_CR125","doi-asserted-by":"crossref","unstructured":"Yue, Y., Finley, T., Radlinski, F., & Joachims, T. (2007). A support vector method for optimizing average precision. In Proceedings of the annual international ACM SIGIR conference on research and development in information retrieval (pp. 271\u2013278). ACM.","DOI":"10.1145\/1277741.1277790"},{"key":"1308_CR126","doi-asserted-by":"crossref","unstructured":"Zhang, G., Kan, M., Shan, S., & Chen, X. (2018a). Generative adversarial network with spatial attention for face attribute editing. In Proceedings of the European conference on computer vision (ECCV) (pp. 417\u2013432).","DOI":"10.1007\/978-3-030-01231-1_26"},{"key":"1308_CR127","doi-asserted-by":"crossref","unstructured":"Zhang, J., Shu, Y., Xu, S., Cao, G., Zhong, F., Liu, M., & Qin, X. (2018b). Sparsely grouped multi-task generative adversarial networks for facial attribute manipulation. In ACM Multimedia conference on multimedia conference (ACMMM) (pp. 392\u2013401). ACM.","DOI":"10.1145\/3240508.3240594"},{"key":"1308_CR128","unstructured":"Zhang, J., Zhong, F., Cao, G., & Qin, X. (2017a). ST-GAN: Unsupervised facial image semantic transformation using generative adversarial networks. In Proceedings of the Asian conference on machine learning (ACML) (pp. 248\u2013263)."},{"key":"1308_CR129","doi-asserted-by":"crossref","unstructured":"Zhang, N., Paluri, M., Ranzato, M., Darrell, T., & Bourdev, L. (2014). Panda: Pose aligned networks for deep attribute modeling. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1637\u20131644). IEEE.","DOI":"10.1109\/CVPR.2014.212"},{"issue":"3","key":"1308_CR130","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/TIFS.2017.2763119","volume":"13","author":"S Zhang","year":"2018","unstructured":"Zhang, S., He, R., Sun, Z., & Tan, T. (2018c). Demeshnet: Blind face inpainting for deep meshface verification. IEEE Transactions on Information Forensics and Security (TIFS), 13(3), 637\u2013647.","journal-title":"IEEE Transactions on Information Forensics and Security (TIFS)"},{"key":"1308_CR131","unstructured":"Zhang, Y. (2018). Xogan: One-to-many unsupervised image-to-image translation. arXiv preprint arXiv:1805.07277."},{"key":"1308_CR132","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Song, Y., & Qi, H. (2017b). Age progression\/regression by conditional adversarial autoencoder. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) (Vol.\u00a02, pp. 4352\u20134360).","DOI":"10.1109\/CVPR.2017.463"},{"key":"1308_CR133","unstructured":"Zhong, Y., Sullivan, J., & Li, H. (2016a). Face attribute prediction using off-the-shelf CNN features. In Proceedings of the IEEE international conference on biometrics (ICB) (pp. 1\u20137). IEEE."},{"key":"1308_CR134","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Sullivan, J., & Li, H. (2016b). Leveraging mid-level deep representations for predicting face attributes in the wild. In Proceedings of the IEEE international conference on image processing (ICIP) (pp. 3239\u20133243). IEEE.","DOI":"10.1109\/ICIP.2016.7532958"},{"key":"1308_CR135","unstructured":"Zhou, S., Xiao, T., Yang, Y., Feng, D., He, Q., & He, W. (2017). Genegan: Learning object transfiguration and attribute subspace from unpaired data. In Proceedings of the British machine vision conference (BMVC)."},{"key":"1308_CR136","doi-asserted-by":"crossref","unstructured":"Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2017). Unpaired image-to-image translation using cycle-consistent adversarial networks. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 2242\u20132251).","DOI":"10.1109\/ICCV.2017.244"},{"key":"1308_CR137","doi-asserted-by":"crossref","unstructured":"Zhuang, N., Yan, Y., Chen, S., & Wang, H. (2018). Multi-task learning of cascaded CNN for facial attribute classification. In Proceedings of the international conference on pattern recognition (ICPR) (pp. 2069\u20132074). IEEE.","DOI":"10.1109\/ICPR.2018.8545271"},{"key":"1308_CR138","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.patcog.2018.03.018","volume":"80","author":"N Zhuang","year":"2018","unstructured":"Zhuang, N., Yan, Y., Chen, S., Wang, H., & Shen, C. (2018). Multi-label learning based deep transfer neural network for facial attribute classification. Pattern Recognition, 80, 225\u2013240.","journal-title":"Pattern Recognition"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01308-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-020-01308-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01308-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T16:17:44Z","timestamp":1666196264000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-020-01308-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,24]]},"references-count":138,"journal-issue":{"issue":"8-9","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["1308"],"URL":"https:\/\/doi.org\/10.1007\/s11263-020-01308-z","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,24]]},"assertion":[{"value":"6 March 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 February 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}