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Found 5 papers, 1 papers with code
Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior
Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance.
Enhancing the Authenticity of Rendered Portraits with Identity-Consistent Transfer Learning
In this paper, we present a novel photo-realistic portrait generation framework that can effectively mitigate the ''uncanny valley'' effect and improve the overall authenticity of rendered portraits.
3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses
We then propose 3DPortraitGAN, the first 3D-aware one-quarter headshot portrait generator that learns a canonical 3D avatar distribution from the 360{\deg}PHQ dataset with body pose self-learning.
LPFF: A Portrait Dataset for Face Generators Across Large Poses
To better validate our pose-conditional 3D-aware generators, we develop a new FID measure to evaluate the 3D-level performance.
HairMapper: Removing Hair From Portraits Using GANs
Removing hair from portrait images is challenging due to the complex occlusions between hair and face, as well as the lack of paired portrait data with/without hair.
