Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …

Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …

In this paper, we propose a novel method, namely GR-PSN, which learns surface normals
from photometric stereo images and generates the photometric images under distant …

Photometric stereo faces challenges from non-Lambertian reflectance in real-world
scenarios. Systematically measuring the reliability of photometric stereo methods in …

Photometric stereo is a well-established technique to estimate the surface normal of an
object. However the requirement of capturing multiple high dynamic range images under …

Uncalibrated photometric stereo (UPS) is challenging due to the inherent ambiguity brought
by the unknown light. Although the ambiguity is alleviated on non-Lambertian objects, the …

Photometric stereo aims to recover detailed surface shapes from images captured under
varying illuminations. However, existing real-world datasets primarily focus on evaluating …

Lack of rigorous reproducibility and validation are significant hurdles for scientific
development across many fields. Materials science, in particular, encompasses a variety of …

Surface texture measurement helps control the quality of large workpieces produced by
machine systems. Current optical measurement methods, eg, fringe projection profilometry …

Photometric Stereo (PS) addresses the challenge of reconstructing a three-dimensional (3D)
representation of an object by estimating the 3D normals at all points on the object's surface …