We present a new data-driven approach with physics-based priors to scene-level normal
estimation from a single polarization image. Existing shape from polarization (SfP) works …

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 …

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 …

Ellipsometry techniques allow to measure polarization information of materials, requiring
precise rotations of optical components with different configurations of lights and sensors …

This study reviews the recent advances in data-driven polarimetric imaging technologies
based on a wide range of practical applications. The widespread international research and …

Multi-view inverse rendering is the problem of estimating the scene parameters such as
shapes materials or illuminations from a sequence of images captured under different …

Indirect time-of-flight (iToF) imaging allows us to capture dense depth information at a low
cost. However, iToF imaging often suffers from multipath interference (MPI) artifacts in the …

This paper proposes a novel polarization sensor structure and network architecture to obtain
a high-quality RGB image and polarization information. Conventional polarization sensors …

We present a method for 3D reconstruction only using calibrated multi-view surface azimuth
maps. Our method, multi-view azimuth stereo, is effective for textureless or specular …

Abstract Shape from Polarization (SfP) aims to recover surface normal using the polarization
cues of light. The accuracy of existing SfP methods is affected by two main problems. First …