CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
Motivated by the intuition that one can transform two aligned point clouds to each other more easily and meaningfully than a misaligned pair, we propose CorrNet3D – the first unsupervised and end-to-end deep learning-based framework – to drive the learning of dense correspondence between 3D shapes by means of deformation-like …