Reconstructing the 3D shape of an object using several images under different light sources
is a very challenging task, especially when realistic assumptions such as light propagation …

Intrinsic decomposition from a single image is a highly challenging task, due to its inherent
ambiguity and the scarcity of training data. In contrast to traditional fully supervised learning …

This paper studies the discontinuity preservation problem in recovering a surface from its
surface normal map. To model discontinuities, we introduce the assumption that the surface …

Reconstructing the 3D shape of an object using several images under different light sources
is a very challenging task, especially when realistic assumptions such as light propagation …

In this work we propose a novel, highly practical, binocular photometric stereo (PS)
framework, which has same acquisition speed as single view PS, however significantly …

Three-dimensional reconstruction of objects from shading information is a challenging task
in computer vision. As most of the approaches facing the Photometric Stereo problem use …

This paper presents a surface normal integration method that solves an inverse problem of
local plane fitting. Surface reconstruction from normal maps is essential in photometric …

We introduce the first end-to-end learning-based solution to near-field Photometric Stereo
(PS), where the light sources are close to the object of interest. This setup is especially …

We present a novel 3D face reconstruction technique that leverages sparse photometric
stereo (PS) and latest advances on face registration/modeling from a single image. We …

The need for an efficient method of integration of a dense normal field is inspired by several
computer vision tasks, such as shape-from-shading, photometric stereo, deflectometry …