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In Proceedings of International Conference on Learning Representations Workshops."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70096-0_22"},{"key":"e_1_3_2_2_32_1","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.","author":"Menon Sachit","year":"2020","unstructured":"Sachit Menon , Alexandru Damian , Shijia Hu , Nikhil Ravi , and Cynthia Rudin . 2020 . PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models . In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Sachit Menon, Alexandru Damian, Shijia Hu, Nikhil Ravi, and Cynthia Rudin. 2020. PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models. 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In Proceedings of Neural Information Processing Systems."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3414685.3417826"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_16"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00209"},{"key":"e_1_3_2_2_37_1","volume-title":"Bogdan Raducanu, and Jose M \u00c1lvarez.","author":"Perarnau Guim","year":"2016","unstructured":"Guim Perarnau , Joost Van De Weijer , Bogdan Raducanu, and Jose M \u00c1lvarez. 2016 . Invertible conditional gans for image editing. arXiv preprint arXiv:1611.06355 (2016). Guim Perarnau, Joost Van De Weijer, Bogdan Raducanu, and Jose M \u00c1lvarez. 2016. 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In Proceedings of International Conference on Machine Learning."},{"volume-title":"Proceedings of International Conference on Learning Representations.","author":"Wang Binxu","key":"e_1_3_2_2_52_1","unstructured":"Binxu Wang and Carlos R. Ponce . 2021. The Geometry of Deep Generative Image Models and its Applications . In Proceedings of International Conference on Learning Representations. Binxu Wang and Carlos R. Ponce. 2021. The Geometry of Deep Generative Image Models and its Applications. In Proceedings of International Conference on Learning Representations."},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475226"},{"key":"e_1_3_2_2_54_1","volume-title":"Black-Box GANs. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.","author":"Wang Hui-Po","year":"2021","unstructured":"Hui-Po Wang , Ning Yu , and Mario Fritz . 2021 b. Hijack-GAN: Unintended-Use of Pretrained , Black-Box GANs. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Hui-Po Wang, Ning Yu, and Mario Fritz. 2021b. Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_3_2_2_55_1","volume-title":"High-Fidelity GAN Inversion for Image Attribute Editing. arXiv preprint arXiv:2109.06590","author":"Wang Tengfei","year":"2021","unstructured":"Tengfei Wang , Yong Zhang , Yanbo Fan , Jue Wang , and Qifeng Chen . 2021c. High-Fidelity GAN Inversion for Image Attribute Editing. arXiv preprint arXiv:2109.06590 ( 2021 ). Tengfei Wang, Yong Zhang, Yanbo Fan, Jue Wang, and Qifeng Chen. 2021c. High-Fidelity GAN Inversion for Image Attribute Editing. arXiv preprint arXiv:2109.06590 (2021)."},{"key":"e_1_3_2_2_56_1","volume-title":"A Simple Baseline for StyleGAN Inversion. arXiv preprint arXiv:2104.07661","author":"Wei Tianyi","year":"2021","unstructured":"Tianyi Wei , Dongdong Chen , Wenbo Zhou , Jing Liao , Weiming Zhang , Lu Yuan , Gang Hua , and Nenghai Yu. 2021. A Simple Baseline for StyleGAN Inversion. arXiv preprint arXiv:2104.07661 ( 2021 ). Tianyi Wei, Dongdong Chen, Wenbo Zhou, Jing Liao, Weiming Zhang, Lu Yuan, Gang Hua, and Nenghai Yu. 2021. A Simple Baseline for StyleGAN Inversion. arXiv preprint arXiv:2104.07661 (2021)."},{"key":"e_1_3_2_2_57_1","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.","author":"Wu Zongze","year":"2021","unstructured":"Zongze Wu , Dani Lischinski , and Eli Shechtman . 2021 a. StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation . In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Zongze Wu, Dani Lischinski, and Eli Shechtman. 2021a. StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_3_2_2_58_1","volume-title":"StyleAlign: Analysis and Applications of Aligned StyleGAN Models. arXiv preprint arXiv:2110.11323","author":"Wu Zongze","year":"2021","unstructured":"Zongze Wu , Yotam Nitzan , Eli Shechtman , and Dani Lischinski . 2021b. StyleAlign: Analysis and Applications of Aligned StyleGAN Models. arXiv preprint arXiv:2110.11323 ( 2021 ). Zongze Wu, Yotam Nitzan, Eli Shechtman, and Dani Lischinski. 2021b. StyleAlign: Analysis and Applications of Aligned StyleGAN Models. arXiv preprint arXiv:2110.11323 (2021)."},{"key":"e_1_3_2_2_59_1","volume-title":"GAN Inversion: A Survey. arXiv preprint arXiv:2101.05278","author":"Xia Weihao","year":"2021","unstructured":"Weihao Xia , Yulun Zhang , Yujiu Yang , Jing-Hao Xue , Bolei Zhou , and Ming-Hsuan Yang . 2021. GAN Inversion: A Survey. arXiv preprint arXiv:2101.05278 ( 2021 ). Weihao Xia, Yulun Zhang, Yujiu Yang, Jing-Hao Xue, Bolei Zhou, and Ming-Hsuan Yang. 2021. GAN Inversion: A Survey. arXiv preprint arXiv:2101.05278 (2021)."},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475633"},{"key":"e_1_3_2_2_61_1","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.","author":"Zhang Richard","year":"2018","unstructured":"Richard Zhang , Phillip Isola , Alexei A. Efros , Eli Shechtman , and Oliver Wang . 2018 . The Unreasonable Effectiveness of Deep Features as a Perceptual Metric . In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang. 2018. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58520-4_35"},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46454-1_36"},{"key":"e_1_3_2_2_64_1","volume-title":"Improved StyleGAN Embedding: Where are the Good Latents? arXiv preprint arXiv:2012.09036","author":"Zhu Peihao","year":"2020","unstructured":"Peihao Zhu , Rameen Abdal , Yipeng Qin , and Peter Wonka . 2020a. Improved StyleGAN Embedding: Where are the Good Latents? arXiv preprint arXiv:2012.09036 ( 2020 ). Peihao Zhu, Rameen Abdal, Yipeng Qin, and Peter Wonka. 2020a. 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