MOCHI enables registration-free training of multi-view 3D face reconstruction by enforcing topological consistency via a pseudo-linear inverse kinematic solver, using synthetic-data-trained 2D landmarks for alignment, and new pointmap/normal losses plus test-time optimization to outperform prior art
Ex- pression invariant 3d face recognition with a morphable model.2008 8th IEEE International Conference on Auto- matic Face & Gesture Recognition, pages 1–6, 2008
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Registration-Free Learnable Multi-View Capture of Faces in Dense Semantic Correspondence
MOCHI enables registration-free training of multi-view 3D face reconstruction by enforcing topological consistency via a pseudo-linear inverse kinematic solver, using synthetic-data-trained 2D landmarks for alignment, and new pointmap/normal losses plus test-time optimization to outperform prior art