Jing Meng

MDND: Unsupervised Learning Guided by Non-Differentiable Refinement for Shape Correspondence

Deep functional map frameworks (DFM) for shape correspondence are powerful, yet fundamentally limited by their reliance on end-to-end differentiability. This constraint prevents the integration of highly accurate, non-differentiable refinement techniques, capping their overall performance, especiall