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cs.CV2026

GNM Head: A Generative aNthropometric Model of the human head

Stylianos Ploumpis, Jan Bednarik, Gaspard Zoss +28

Parametric models of the human head are essential tools traditionally used in computer vision and graphics for animation, rendering, and reconstruction. More recently, they serve a…

cs.CV2026

Topologically Consistent Multi-view 3D Head Reconstruction via Coarse-Guided Layered Surface Sampling

Timo Bolkart, Daoye Wang, Prashanth Chandran

We present SHELLS (Semantic Head Estimation via Layered Local Sampling), an efficient feed-forward framework for 3D head reconstruction in dense semantic correspondence from multi-…

cs.CV2026

Representing 3D Faces with Learnable B-Spline Volumes

Prashanth Chandran, Daoye Wang, Timo Bolkart

We present CUBE (Control-based Unified B-spline Encoding), a new geometric representation for human faces that combines B-spline volumes with learned features, and demonstrate its…

cs.CV2024

Learning to Stabilize Faces

Jan Bednarik, Erroll Wood, Vasileios Choutas +4

Nowadays, it is possible to scan faces and automatically register them with high quality. However, the resulting face meshes often need further processing: we need to stabilize the…

cs.CV2024

Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures

Marcel C. Bühler, Gengyan Li, Erroll Wood +13

Volumetric modeling and neural radiance field representations have revolutionized 3D face capture and photorealistic novel view synthesis. However, these methods often require hund…