SVRecon predicts coarse voxel occupancies and builds sparse high-resolution feature volumes only near surfaces, enabling 512^3 generalizable reconstruction with over 50x less storage than dense-volume methods.
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High-Fidelity and Generalizable Neural Surface Reconstruction with Sparse Feature Volumes
SVRecon predicts coarse voxel occupancies and builds sparse high-resolution feature volumes only near surfaces, enabling 512^3 generalizable reconstruction with over 50x less storage than dense-volume methods.