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Found 3 papers, 2 papers with code
Implicit Shape and Appearance Priors for Few-Shot Full Head Reconstruction
Recent advancements in learning techniques that employ coordinate-based neural representations have yielded remarkable results in multi-view 3D reconstruction tasks.
SIRA: Relightable Avatars from a Single Image
Our key ingredients are two data-driven statistical models based on neural fields that resolve the ambiguities of single-view 3D surface reconstruction and appearance factorization.
H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction
In this paper, we tackle these limitations for the specific problem of few-shot full 3D head reconstruction, by endowing coordinate-based representations with a probabilistic shape prior that enables faster convergence and better generalization when using few input images (down to three).
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