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cs.CV2025
Pix2NPHM: Learning to Regress NPHM Reconstructions From a Single Image
Simon Giebenhain, Tobias Kirschstein, Liam Schoneveld +3
Neural Parametric Head Models (NPHMs) are a recent advancement over mesh-based 3d morphable models (3DMMs) to facilitate high-fidelity geometric detail. However, fitting NPHMs to v…
cs.CV2025
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians
Liam Schoneveld, Zhe Chen, Davide Davoli +4
Accurate, real-time 3D reconstruction of human heads from monocular images and videos underlies numerous visual applications. As 3D ground truth data is hard to come by at scale, p…