[PDF][PDF] Deep Learning Methods for Calibrated Photometric Stereo and Beyond
Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …
varying shading cues, ie, modeling the relationship between surface orientation and …
A neural height-map approach for the binocular photometric stereo problem
F Logothetis, I Budvytis… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
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 …
framework, which has same acquisition speed as single view PS, however significantly …
Sparse Views Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo
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 …
they require either a fairly dense sampling of the viewing sphere or pre-training on an …
Neural Brdf Plugin for Unsupervised Photometric Stereo
Recovering surface normal under unknown general reflectance is challenging for
photometric stereo. Supervised learning-based methods implicitly handle general …
photometric stereo. Supervised learning-based methods implicitly handle general …