Get 3D object shape using SDF and generalized multi-scale volume representation with GenS
Get 3D object shape using SDF and generalized multi-scale volume representation with GenS
GenS: Generalizable Neural Surface Reconstruction from Multi-View Images
arXiv paper abstract https://arxiv.org/abs/2406.02495
arXiv PDF paper https://arxiv.org/pdf/2406.02495
... signed distance function (SDF) and differentiable volume rendering ... powerful ... for surface reconstruction from multi-view images without 3D supervision. However ... impeded by ... long-time per-scene optimizations and cannot generalize to new scenes.
... present GenS, an end-to-end generalizable neural surface reconstruction model. Unlike coordinate-based methods that train a separate network for each scene, ... construct a generalized multi-scale volume to directly encode all scenes.
... introduce a multi-scale feature-metric consistency to impose the multi-view consistency in a more discriminative multi-scale feature space, which is robust to the failures of the photometric consistency.
And the learnable feature can be self-enhanced to continuously improve the matching accuracy and mitigate aggregation ambiguity.
... design a view contrast loss to force the model to be robust to those regions covered by few viewpoints through distilling the geometric prior from dense input to sparse input.
... model can generalize well to new scenes and outperform existing state-of-the-art methods even those employing ground-truth depth supervision ...
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