Unsupervised deep functional map method with novel loss coupling functional and point-wise maps for robust 3D shape matching on non-isometric, partial, and noisy shapes.
arXiv preprint arXiv:2012.00888 (2020)
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A self-supervised multimodal approach for non-rigid 3D shape matching that achieves state-of-the-art results on benchmarks and previously unseen cross-dataset generalization.
Introduces self-adaptive functional map solver and vertex-wise contrastive loss for improved unsupervised non-rigid 3D shape matching on challenging datasets.
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Unsupervised deep functional map method with novel loss coupling functional and point-wise maps for robust 3D shape matching on non-isometric, partial, and noisy shapes.
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