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In this paper, we present an integrated system for automatically generating and editing face images through face swapping, attribute-based editing, and random face parts synthesis.
Long short-term memory
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A morphable model for the synthesis of 3d faces
Blanz, V., Vetter, T.: · 1999
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Expressive expression mapping with ratio images
Liu, Z., Shan, Y., Zhang, Z.: · 2001
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Active appearance models
Cootes, T.F., Edwards, G.J., Taylor, C.J.: · 2001
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Multiscale structural similarity for image quality assessment
Wang, Z., Simoncelli, E.P., Bovik, A.C.: · 2003
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Exchanging faces in images
Blanz, V., Scherbaum, K., Vetter, T., Seidel, H.P.: · 2004
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Seamless image stitching in the gradient domain
Levin, A., Zomet, A., Peleg, S., Weiss, Y.: · 2004
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Face swapping: automatically replacing faces in photographs
Bitouk, D., Kumar, N., Dhillon, S., Belhumeur, P., Nayar, S.K.: · 2008
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Data-driven enhancement of facial attractiveness
Leyvand, T., Cohen-Or, D., Dror, G., Lischinski, D.: · 2008
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Dlib-ml: A machine learning toolkit
King, D.E.: · 2009
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Expression flow for 3d-aware face component transfer
Yang, F., Wang, J., Shechtman, E., Bourdev, L., Metaxas, D.: · 2011
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Single-view hair modeling for portrait manipulation
Chai, M., Wang, L., Weng, Y., Yu, Y., Guo, B., Zhou, K.: · 2012
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Viewing real-world faces in 3d
Hassner, T.: · 2013
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Facewarehouse: A 3d facial expression database for visual computing
Cao, C., Weng, Y., Zhou, S., Tong, Y., Zhou, K.: · 2014
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Photorealistic face de-identification by aggregating donors’ face components
Mosaddegh, S., Simon, L., Jurie, F.: · 2014
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Semi-supervised learning with deep generative models
Kingma, D.P., Mohamed, S., Rezende, D.J., Welling, M.: · 2014
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: · 2014
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Adam: A Method for Stochastic Optimization
Kingma, D.P., Ba, J.: · 2014
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Deep learning face attributes in the wild
Liu, Z., Luo, P., Wang, X., Tang, X.: · 2015
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Data-augmentation for reducing dataset bias in person re-identification
McLaughlin, N., Martinez-del Rincon, J., Miller, P.: · 2015
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High-quality hair modeling from a single portrait photo
Chai, M., Luo, L., Sunkavalli, K., Carr, N., Hadap, S., Zhou, K.: · 2015
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Autoencoding beyond pixels using a learned similarity metric
Larsen, A.B.L., Kaae Sønderby, S., Larochelle, H., Winther, O.: · 2015
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Adversarially learned inference
Dumoulin, V., Belghazi, I., Poole, B., Lamb, A., Arjovsky, M., Mastropietro, O., Courville, A.: · 2016
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Generating images part by part with composite generative adversarial networks
Kwak, H., Zhang, B.T.: · 2016
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Portrait lighting transfer using a mass transport approach
Shu, Z., Hadap, S., Shechtman, E., Sunkavalli, K., Paris, S., Samaras, D.: · 2017
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Example-based synthesis of stylized facial animations
Fišer, J., Jamriška, O., Simons, D., Shechtman, E., Lu, J., Asente, P., Lukáč, M., Sýkora, D.: · 2017
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CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training
Bao, J., Chen, D., Wen, F., Li, H., Hua, G.: · 2017
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Gregor, K., Danihelka, I., Graves, A., Jimenez Rezende, D., Wierstra, D.: · 2015
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Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks
Zhang, K., Zhang, Z., Li, Z., Qiao, Y.: · 2016
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Transfiguring portraits
Kemelmacher-Shlizerman, I.: · 2016
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Fast face-swap using convolutional neural networks
Korshunova, I., Shi, W., Dambre, J., Theis, L.: · 2016
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Do we really need to collect millions of faces for effective face recognition?
Masi, I., an Trãn, A.T., Hassner, T., Leksut, J.T., Medioni, G.: · 2016
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Image style transfer using convolutional neural networks
Gatys, L.A., Ecker, A.S., Bethge, M.: · 2016
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OpenFace: A general-purpose face recognition library with mobile applications
Amos, B., Ludwiczuk, B., Satyanarayanan, M.: · 2016
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Neural face editing with intrinsic image disentangling
Shu, Z., Yumer, E., Hadap, S., Sunkavalli, K., Shechtman, E., Samaras, D.: · 2017
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StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Choi, Y., Choi, M., Kim, M., Ha, J.W., Kim, S., Choo, J.: · 2017
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Globally and locally consistent image completion
Iizuka, S., Simo-Serra, E., Ishikawa, H.: · 2017
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Image-to-image translation with conditional adversarial networks
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: · 2017
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Variational Approaches for Auto-Encoding Generative Adversarial Networks
Rosca, M., Lakshminarayanan, B., Warde-Farley, D., Mohamed, S.: · 2017
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LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
Yang, J., Kannan, A., Batra, D., Parikh, D.: · 2017
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
Karras, T., Aila, T., Laine, S., Lehtinen, J.: · 2017
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On face segmentation, face swapping, and face perception
Nirkin, Y., Masi, I., Tran, A.T., Hassner, T., Medioni, G.: · 2018
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https://www.fakeapp.org/ (2018)
FakeApp: · 2018
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Chen, Z., Nie, S., Wu, T., Healey, C.G.: · 2018
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Global and Local Consistent Age Generative Adversarial Networks
Li, P., Hu, Y., Li, Q., He, R., Sun, Z.: · 2018
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