This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …

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 aims to recover the surface normals of a 3D object from various shading
cues, establishing the relationship between two-dimensional images and the object …

Acquiring high-resolution 3D surface structures is a crucial task in computer vision as it
provides more detailed surface textures and clearer structures. Photometric stereo can …

Recent progress on photometric stereo extends the technique to deal with general materials
and unknown illumination conditions. However, due to the lack of suitable benchmark data …

We present a deep learning approach to reconstruct scene appearance from unstructured
images captured under collocated point lighting. At the heart of Deep Reflectance Volumes …

This paper addresses the problem of photometric stereo for non-Lambertian surfaces.
Existing approaches often adopt simplified reflectance models to make the problem more …

This paper proposes an uncalibrated photometric stereo method for non-Lambertian scenes
based on deep learning. Unlike previous approaches that heavily rely on assumptions of …

Most conventional photometric stereo algorithms inversely solve a BRDF-based image
formation model. However, the actual imaging process is often far more complex due to the …

Photorealistic rendering of real world environments is important in a range of different areas;
including Visual Special effects, Interior/Exterior Modelling, Architectural Modelling, Cultural …