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dc.contributor.authorJiang, Diqiongen_US
dc.contributor.authorYou, Lihuaen_US
dc.contributor.authorChang, Jianen_US
dc.contributor.authorTong, Ruofengen_US
dc.contributor.editorYang, Yinen_US
dc.contributor.editorParakkat, Amal D.en_US
dc.contributor.editorDeng, Bailinen_US
dc.contributor.editorNoh, Seung-Taken_US
dc.description.abstractHigh-quality and personalized digital human faces have been widely used in media and entertainment, from film and game production to virtual reality. However, the existing technology of generating digital faces requires extremely intensive labor, which prevents the large-scale popularization of digital face technology. In order to tackle this problem, the proposed research will investigate deep learning-based facial modeling and animation technologies to 1) create personalized face geometry from a single image, including the recognizable neutral face shape and believable personalized blendshapes; (2) generate personalized production-level facial skin textures from a video or image sequence; (3) automatically drive and animate a 3D target avatar by an actor's 2D facial video or audio. Our innovation is to achieve these tasks both efficiently and precisely by using the end-to-end framework with modern deep learning technology (StyleGAN, Transformer, NeRF).en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.titleDFGA: Digital Human Faces Generation and Animation from the RGB Video using Modern Deep Learning Technologyen_US
dc.description.seriesinformationPacific Graphics Short Papers, Posters, and Work-in-Progress Papers
dc.description.sectionheadersDigital Human
dc.identifier.pages2 pages

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License