Get 3D object shape with few views by learning surface geometry with NeuSurf
Get 3D object shape with few views by learning surface geometry with NeuSurf
NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views
arXiv paper abstract https://arxiv.org/abs/2312.13977
arXiv PDF paper https://arxiv.org/pdf/2312.13977.pdf
... neural implicit functions ... demonstrated remarkable results in ... multi-view reconstruction ... However, most ... methods are ... for dense views and exhibit unsatisfactory performance ... with sparse views.
... propose a novel sparse view reconstruction framework that leverages on-surface priors to achieve highly faithful surface reconstruction.
... design several constraints on global geometry alignment and local geometry refinement for jointly optimizing coarse shapes and fine details.
... train a neural network to learn a global implicit field from the on-surface points obtained from SfM and then leverage it as a coarse geometric constraint.
To exploit local geometric consistency, ... project on-surface points onto seen and unseen views, treating the consistent loss of projected features as a fine geometric constraint.
... demonstrate significant improvements over the state-of-the-art methods.
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