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Coarse-to-Fine: A Hybrid Self-Supervised Method for Non-rigid 3D Shape Matching

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Non-rigid 3D shape matching is a fundamental task in computer vision and graphics. In this paper, we propose a hybrid self-supervised method based on a coarse-to-fine strategy, which ensures consistency between the coarse mapping and the refined correspondence produced by our refinement module.

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