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The vast majority of existing techniques do not provide such intuitive and fine-grained control, or only enable coarse editing of a single isolated control parameter. Very recently, high-quality semantically controlled editing has been demonstrated, however only on synthetically created StyleGAN images. We present the first approach for embedding real portrait images in the latent space of StyleGAN, which allows for intuitive editing of the head pose, facial expression, and scene illumination in the image. Semantic editing in parameter space is achieved based on StyleRig, a pretrained neural network that maps the control space of a 3D morphable face model to the latent space of the GAN. We design a novel hierarchical non-linear optimization problem to obtain the embedding. An identity preservation energy term allows spatially coherent edits while maintaining facial integrity. Our approach runs at interactive frame rates and thus allows the user to explore the space of possible edits. We evaluate our approach on a wide set of portrait photos, compare it to the current state of the art, and validate the effectiveness of its components in an ablation study.<\/jats:p>","DOI":"10.1145\/3414685.3417803","type":"journal-article","created":{"date-parts":[[2020,11,27]],"date-time":"2020-11-27T21:51:05Z","timestamp":1606513865000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":123,"title":["PIE"],"prefix":"10.1145","volume":"39","author":[{"given":"Ayush","family":"Tewari","sequence":"first","affiliation":[{"name":"Max Planck Institute for Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Elgharib","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mallikarjun B","family":"R","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florian","family":"Bernard","sequence":"additional","affiliation":[{"name":"SIC and Technical University of Munich"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hans-Peter","family":"Seidel","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"P\u00e9rez","sequence":"additional","affiliation":[{"name":"Valeo.ai"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Zollh\u00f6fer","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Theobalt","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,11,27]]},"reference":[{"key":"e_1_2_2_1_1","unstructured":"Mart\u00edn Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. 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StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows. arXiv:2008.02401 [cs.CV]  Rameen Abdal Peihao Zhu Niloy Mitra and Peter Wonka. 2020b. StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows. arXiv:2008.02401 [cs.CV]","DOI":"10.1145\/3447648"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCG.2010.65"},{"key":"e_1_2_2_6_1","volume-title":"Cohen","author":"Averbuch-Elor Hadar","year":"2017","unstructured":"Hadar Averbuch-Elor , Daniel Cohen-Or , Johannes Kopf , and Michael F . Cohen . 2017 . Bringing Portraits to Life. ACM Transactions on Graphics (Proceeding of SIGGRAPH Asia 2017) 36, 6 (2017), 196. Hadar Averbuch-Elor, Daniel Cohen-Or, Johannes Kopf, and Michael F. Cohen. 2017. Bringing Portraits to Life. 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Ayush Tewari, Michael Zoll\u00f6fer, Hyeongwoo Kim, Pablo Garrido, Florian Bernard, Patrick Perez, and Theobalt Christian. 2017. MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction. In The IEEE International Conference on Computer Vision (ICCV)."},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3323035"},{"key":"e_1_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Justus Thies M. Zollh\u00f6fer M. Stamminger C. Theobalt and M. Nie\u00dfner. 2016. Face2Face: Real-time Face Capture and Reenactment of RGB Videos. In CVPR.  Justus Thies M. Zollh\u00f6fer M. Stamminger C. Theobalt and M. Nie\u00dfner. 2016. Face2Face: Real-time Face Capture and Reenactment of RGB Videos. In CVPR.","DOI":"10.1109\/CVPR.2016.262"},{"key":"e_1_2_2_42_1","unstructured":"Ting-Chun Wang Ming-Yu Liu Andrew Tao Guilin Liu Jan Kautz and Bryan Catanzaro. 2019a. Few-shot Video-to-Video Synthesis. In Advances in Neural Information Processing Systems (NeurIPS).  Ting-Chun Wang Ming-Yu Liu Andrew Tao Guilin Liu Jan Kautz and Bryan Catanzaro. 2019a. Few-shot Video-to-Video Synthesis. In Advances in Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_2_2_43_1","volume-title":"Video-to-Video Synthesis. In Proc. NeurIPS.","author":"Wang Ting-Chun","year":"2019","unstructured":"Ting-Chun Wang , Ming-Yu Liu , Jun-Yan Zhu , Guilin Liu , Andrew Tao , Jan Kautz , and Bryan Catanzaro . 2019 b. Video-to-Video Synthesis. In Proc. NeurIPS. Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz, and Bryan Catanzaro. 2019b. Video-to-Video Synthesis. In Proc. NeurIPS."},{"key":"e_1_2_2_44_1","volume-title":"European Conference on Computer Vision.","author":"Wiles O.","unstructured":"O. Wiles , A.S. Koepke , and A. Zisserman . 2018. X2Face: A network for controlling face generation by using images, audio, and pose codes . In European Conference on Computer Vision. 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