6 papers
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…
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-…
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…
Pixels2Points: Fusing 2D and 3D Features for Facial Skin Segmentation
Victoria Yue Chen, Daoye Wang, Stephan Garbin +4
Face registration deforms a template mesh to closely fit a 3D face scan, the quality of which commonly degrades in non-skin regions (e.g., hair, beard, accessories), because the op…
GroomCap: High-Fidelity Prior-Free Hair Capture
Yuxiao Zhou, Menglei Chai, Daoye Wang +5
Despite recent advances in multi-view hair reconstruction, achieving strand-level precision remains a significant challenge due to inherent limitations in existing capture pipeline…
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…