Photometric stereo aims to recover detailed surface shapes from images captured under
varying illuminations. However, existing real-world datasets primarily focus on evaluating …

At present, there are two obvious problems in radar-based gait recognition. First, the
traditional radar frequency band is difficult to meet the requirements of fine identification with …

Photometric stereo faces challenges from non-Lambertian reflectance in real-world
scenarios. Systematically measuring the reliability of photometric stereo methods in …

Photometric stereo (PS) techniques nowadays remain constrained to an ideal laboratory
setup where modeling and calibration of lighting is amenable. To eliminate such restrictions …

Neural approaches have shown a significant progress on camera-based reconstruction. But
they require either a fairly dense sampling of the viewing sphere or pre-training on an …

This paper presents a photometric stereo method that works with unknown natural
illumination without any calibration objects or initial guess of the target shape. To solve this …

We propose a method to estimate the bidirectional reflectance distribution function (BRDF)
and shading of complete scenes under static illumination given the 3D scene geometry and …

Abstract Three-dimensional (3D) measurement provides essential geometric information for
quality control and process monitoring in many manufacturing applications. Photometric …

This paper presents 'DeepShadow', a one-shot method for recovering the depth map and
surface normals from photometric stereo shadow maps. Previous works that try to recover …

We propose an approach for optimizing high-quality clothed human body shapes in minutes,
using multi-view posed images. While traditional neural rendering methods struggle to …