Self-supervised monocular depth estimation networks are trained to predict scene depth
using nearby frames as a supervision signal during training. However, for many …

Applications of mobile robots are continuously capturing the importance in numerous areas
such as agriculture, surveillance, defense, and planetary exploration to name a few …

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 …

This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the
realm of deep learning. The previous state-of-the-art methods for SfP have been purely …

Reconstructing an object's geometry and appearance from multiple images, also known as
inverse rendering, is a fundamental problem in computer graphics and vision. Inverse …

In this paper, we propose a hybrid depth imaging system in which a polarisation camera is
augmented by a second image from a standard digital camera. For this modest increase in …

This paper tackles the problem of estimating 3D body shape of clothed humans from single
polarized 2D images, ie polarization images. Polarization images are known to be able to …

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 …

Polarisation Filter Array (PFA) cameras allow the analysis of light polarisation state in a
simple and cost-effective manner. Such filter arrays work as the Bayer pattern for colour …

Neural implicit surface reconstruction has achieved remarkable progress recently. Despite
resorting to complex radiance modeling, state-of-the-art methods still struggle with …