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This paper is on face/head reenactment where the goal is to transfer the facial pose (3D head orientation and expression) of a target face to a source face.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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The first facial landmark tracking in-the-wild challenge: Benchmark and results
Jie Shen, Stefanos Zafeiriou, Grigoris G Chrysos, Jean Kossaifi, Georgios Tzimiropoulos, and Maja Pantic · 2015
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Face alignment across large poses: A 3d solution
Xiangyu Zhu, Zhen Lei, Xiaoming Liu, Hailin Shi, and Stan Z Li · 2016
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How far are we from solving the 2d & 3d face alignment problem?(and a dataset of 230,000 3d facial landmarks)
Adrian Bulat and Georgios Tzimiropoulos · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Voxceleb: a large-scale speaker identification dataset
A. Nagrani, J. S. Chung, and A. Zisserman · 2017
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Towards open-set identity preserving face synthesis
Jianmin Bao, Dong Chen, Fang Wen, Houqiang Li, and Gang Hua · 2018
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Voxceleb2: Deep speaker recognition
J. S. Chung, A. Nagrani, and A. Zisserman · 2018
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FaceForensics: A large-scale video dataset for forgery detection in human faces
Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner · 2018
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Towards accurate generative models of video: A new metric & challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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X2face: A network for controlling face generation using images, audio, and pose codes
Olivia Wiles, A Koepke, and Andrew Zisserman · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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First order motion model for image animation
Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov, Elisa Ricci, and Nicu Sebe · 2019
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Few-shot adversarial learning of realistic neural talking head models
Egor Zakharov, Aliaksandra Shysheya, Egor Burkov, and Victor Lempitsky · 2019
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Neural head reenactment with latent pose descriptors
Egor Burkov, Igor Pasechnik, Artur Grigorev, and Victor Lempitsky · 2020
Cited alongside, same era.
Disentangled and controllable face image generation via 3d imitative-contrastive learning
Yu Deng, Jiaolong Yang, Dong Chen, Fang Wen, and Xin Tong · 2020
Cited alongside, same era.
Headgan: Video-and-audio-driven talking head synthesis
Michail Christos Doukas, Stefanos Zafeiriou, and Viktoriia Sharmanska · 2020
Cited alongside, same era.
GIF: generative interpretable faces
Partha Ghosh, Pravir Singh Gupta, Roy Uziel, Anurag Ranjan, Michael J. Black, and Timo Bolkart · 2020
Cited alongside, same era.
Marionette: Few-shot face reenactment preserving identity of unseen targets
Sungjoo Ha, Martin Kersner, Beomsu Kim, Seokjun Seo, and Dongyoung Kim · 2020
Cited alongside, same era.
Learning an animatable detailed 3d face model from in-the-wild images
Yao Feng, Haiwen Feng, Michael J Black, and Timo Bolkart · 2021
Later among the works it cites.
Learned spatial representations for few-shot talking-head synthesis
Moustafa Meshry, Saksham Suri, Larry S Davis, and Abhinav Shrivastava · 2021
Later among the works it cites.
Large: Latent-based regression through gan semantics
Yotam Nitzan, Rinon Gal, Ofir Brenner, and Daniel Cohen-Or · 2021
Later among the works it cites.
Tensor component analysis for interpreting the latent space of gans
James Oldfield, Markos Georgopoulos, Yannis Panagakis, Mihalis A. Nicolaou, and Ioannis Patras · 2021
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Pirenderer: Controllable portrait image generation via semantic neural rendering
Yurui Ren, Ge Li, Yuanqi Chen, Thomas H Li, and Shan Liu · 2021
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Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
Cited alongside, same era.
Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Config: Controllable neural face image generation
Marek Kowalski, Stephan J. Garbin, Virginia Estellers, Tadas Baltrušaitis, Matthew Johnson, and Jamie Shotton · 2020
Cited alongside, same era.
Face identity disentanglement via latent space mapping
Yotam Nitzan, Amit Bermano, Yangyan Li, and Daniel Cohen-Or · 2020
Cited alongside, same era.
Interfacegan: Interpreting the disentangled face representation learned by gans
Yujun Shen, Ceyuan Yang, Xiaoou Tang, and Bolei Zhou · 2020
Cited alongside, same era.
Icface: Interpretable and controllable face reenactment using gans
Soumya Tripathy, Juho Kannala, and Esa Rahtu · 2020
Cited alongside, same era.
Unsupervised discovery of interpretable directions in the gan latent space
Andrey Voynov and Artem Babenko · 2020
Cited alongside, same era.
Encoding in style: a stylegan encoder for image-to-image translation
Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, and Daniel Cohen-Or · 2021
Later among the works it cites.
Pivotal tuning for latent-based editing of real images
Daniel Roich, Ron Mokady, Amit H Bermano, and Daniel Cohen-Or · 2021
Later among the works it cites.
Closed-form factorization of latent semantics in gans
Yujun Shen and Bolei Zhou · 2021
Later among the works it cites.
Gan-control: Explicitly controllable gans
Alon Shoshan, Nadav Bhonker, Igor Kviatkovsky, and Gerard Medioni · 2021
Later among the works it cites.
Designing an encoder for stylegan image manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, and Daniel Cohen-Or · 2021
Later among the works it cites.
Facegan: Facial attribute controllable reenactment gan
Soumya Tripathy, Juho Kannala, and Esa Rahtu · 2021
Later among the works it cites.
Warpedganspace: Finding non-linear rbf paths in gan latent space
Christos Tzelepis, Georgios Tzimiropoulos, and Ioannis Patras · 2021
Later among the works it cites.
Discovering interpretable latent space directions of gans beyond binary attributes
Huiting Yang, Liangyu Chai, Qiang Wen, Shuang Zhao, Zixun Sun, and Shengfeng He · 2021
Later among the works it cites.
A latent transformer for disentangled face editing in images and videos
Xu Yao, Alasdair Newson, Yann Gousseau, and Pierre Hellier · 2021
Later among the works it cites.
Hyperstyle: Stylegan inversion with hypernetworks for real image editing
Yuval Alaluf, Omer Tov, Ron Mokady, Rinon Gal, and Amit Bermano · 2022
Closest in time.
Hyperinverter: Improving stylegan inversion via hypernetwork
Tan M Dinh, Anh Tuan Tran, Rang Nguyen, and Binh-Son Hua · 2022
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Dual-generator face reenactment
Gee-Sern Hsu, Chun-Hung Tsai, and Hung-Yi Wu · 2022
Closest in time.
Panda: Unsupervised learning of parts and appearances in the feature maps of gans
James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis A Nicolaou, and Ioannis Patras · 2022
Closest in time.
Contraclip: Interpretable gan generation driven by pairs of contrasting sentences
Christos Tzelepis, James Oldfield, Georgios Tzimiropoulos, and Ioannis Patras · 2022
Closest in time.