This repository contains the official implementation of a CVPR 2024 oral paper on surface normal estimation. The method proposes using per-pixel ray direction as input and learning relative rotations between neighboring surface normals as key inductive biases. The approach achieves crisp yet piecewise-smooth predictions across arbitrary image resolutions and demonstrates stronger generalization than recent ViT-based state-of-the-art models while being trained on a much smaller dataset.