SDA-SNE: Spatial Discontinuity-Aware Surface Normal Estimation via Multi-Directional Dynamic Programming. (arXiv:2208.08667v1 [cs.CV])

The state-of-the-art (SoTA) surface normal estimators (SNEs) generally
translate depth images into surface normal maps in an end-to-end fashion.
Although such SNEs have greatly minimized the trade-off between efficiency and
accuracy, their performance on spatial discontinuities, e.g., edges and ridges,
is still unsatisfactory. To address this issue, this paper first introduces a
novel multi-directional dynamic programming strategy to adaptively determine
inliers (co-planar 3D points) by minimizing a (path) smoothness energy. The
depth gradients can then be refined iteratively using a …

arxiv cv discontinuity normal programming