Polarization imaging can retrieve inaccurate objects' 3D shapes with fine textures, whereas
coarse but accurate depths can be provided by binocular stereo vision. To take full …

Stereo depth estimation usually struggles to deal with textureless scenes for both traditional
and learning-based methods due to the inherent dependence on image correspondence …

Polarization has been used to solve a lot of computer vision tasks such as Shape from
Polarization (SfP). But existing methods suffer from ambiguity problems of polarization. To …

The fusion of shape from polarization (SFP) and depth sensors is an effective method for
high-quality 3D reconstruction. However, accurate registration of images from different …

Learning-based depth estimation has witnessed recent progress in multiple directions; from
self-supervision using monocular video to supervised methods offering highest accuracy …

This article presents a new approach for surface normal recovery from polarization images
under an unknown distant light. Polarization provides rich cues of object geometry and …

In this paper we consider the problem of relative pose estimation from two images with per-
pixel polarimetric information. Using these additional measurements we derive a simple …

Photometric 3D-reconstruction techniques aim at inferring the geometry of a scene from one
or several images, by inverting a physical model describing the image formation. This …

Photometric cues play an important role in recovering per-pixel 3D information from images.
Shape from shading and photometric stereo are popular photometric 3D reconstruction …

In this paper we present methods for estimating shape from polarisation and shading
information, ie photo-polarimetric shape estimation, under varying, but unknown …