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Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond., , , , , , , и . Int. J. Comput. Vis., 127 (6-7): 907-929 (2019)AgeDB: The First Manually Collected, In-the-Wild Age Database., , , , , и . CVPR Workshops, стр. 1997-2005. IEEE Computer Society, (2017)3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation., , , , и . CoRR, (2019)Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks., , , , , , и . ECCV (29), том 12374 из Lecture Notes in Computer Science, стр. 415-433. Springer, (2020)Synthesising 3D Facial Motion from "In-the-Wild" Speech., , , , , и . CoRR, (2019)Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning., , , , , , , , , и 2 other автор(ы). CoRR, (2023)MimicME: A Large Scale Diverse 4D Database for Facial Expression Analysis., , , , , , , , , и 8 other автор(ы). ECCV (8), том 13668 из Lecture Notes in Computer Science, стр. 467-484. Springer, (2022)Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks., , , , , , и . CoRR, (2019)Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond., , , , , , , и . CoRR, (2018)3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation., , , , и . Int. J. Comput. Vis., 128 (10): 2534-2551 (2020)