Deep functional maps have recently emerged as a successful paradigm for
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Transfer learning is fundamental for addressing problems in settings wit...
We present Neural Correspondence Prior (NCP), a new paradigm for computi...
In this work, we present a novel learning-based framework that combines ...
Efficient and practical representation of geometric data is a ubiquitous...
We consider the problem of computing dense correspondences between non-r...
We introduce a new approach to deep learning on 3D surfaces, based on th...