Get 3D object from many views as good as scanner using multi-resolution hash encode with SuperNormal
Get 3D object from many views as good as scanner using multi-resolution hash encode with SuperNormal
SuperNormal: Neural Surface Reconstruction via Multi-View Normal Integration
arXiv abstract https://arxiv.org/abs/2312.04803
arXiv PDF paper https://arxiv.org/pdf/2312.04803.pdf
... present SuperNormal, a fast, high-fidelity approach to multi-view 3D reconstruction using surface normal maps.
With a few minutes, SuperNormal produces detailed surfaces on par with 3D scanners.
... harness volume rendering to optimize a neural signed distance function (SDF) powered by multi-resolution hash encoding.
To accelerate training, ... propose directional finite difference and patch-based ray marching to approximate the SDF gradients numerically.
While not compromising reconstruction quality, this strategy is nearly twice as efficient as analytical gradients and about three times faster than axis-aligned finite difference.
... demonstrate the superiority of SuperNormal in efficiency and accuracy compared to existing multi-view photometric stereo methods ... neural 3D reconstruction methods.
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