PVP: Personalized Video Prior for Editable Dynamic Portraits using StyleGAN

dc.contributor.authorLin, Kai-Enen_US
dc.contributor.authorTrevithick, Alexen_US
dc.contributor.authorCheng, Kelien_US
dc.contributor.authorSarkis, Michelen_US
dc.contributor.authorGhafoorian, Mohsenen_US
dc.contributor.authorBi, Ningen_US
dc.contributor.authorReitmayr, Gerharden_US
dc.contributor.authorRamamoorthi, Ravien_US
dc.contributor.editorRitschel, Tobiasen_US
dc.contributor.editorWeidlich, Andreaen_US
dc.date.accessioned2023-06-27T07:03:42Z
dc.date.available2023-06-27T07:03:42Z
dc.date.issued2023
dc.description.abstractPortrait synthesis creates realistic digital avatars which enable users to interact with others in a compelling way. Recent advances in StyleGAN and its extensions have shown promising results in synthesizing photorealistic and accurate reconstruction of human faces. However, previous methods often focus on frontal face synthesis and most methods are not able to handle large head rotations due to the training data distribution of StyleGAN. In this work, our goal is to take as input a monocular video of a face, and create an editable dynamic portrait able to handle extreme head poses. The user can create novel viewpoints, edit the appearance, and animate the face. Our method utilizes pivotal tuning inversion (PTI) to learn a personalized video prior from a monocular video sequence. Then we can input pose and expression coefficients to MLPs and manipulate the latent vectors to synthesize different viewpoints and expressions of the subject. We also propose novel loss functions to further disentangle pose and expression in the latent space. Our algorithm shows much better performance over previous approaches on monocular video datasets, and it is also capable of running in real-time at 54 FPS on an RTX 3080.en_US
dc.description.number4
dc.description.sectionheadersVideo and Editing
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14890
dc.identifier.issn1467-8659
dc.identifier.pages13 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14890
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14890
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Image-based rendering
dc.subjectComputing methodologies
dc.subjectImage
dc.subjectbased rendering
dc.titlePVP: Personalized Video Prior for Editable Dynamic Portraits using StyleGANen_US
Files
Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
v42i4_10_14890.pdf
Size:
49.67 MB
Format:
Adobe Portable Document Format
Description:
Loading...
Thumbnail Image
Name:
pvp_supp_crc.pdf
Size:
68.42 MB
Format:
Adobe Portable Document Format
Collections