[HTML][HTML] Deep learning in optical metrology: a review

C Zuo, J Qian, S Feng, W Yin, Y Li, P Fan… - Light: Science & …, 2022‏ - nature.com
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

Deep learning methods for calibrated photometric stereo and beyond

Y Ju, KM Lam, W **e, H Zhou… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …

Ps-nerf: Neural inverse rendering for multi-view photometric stereo

W Yang, G Chen, C Chen, Z Chen… - European conference on …, 2022‏ - Springer
Traditional multi-view photometric stereo (MVPS) methods are often composed of multiple
disjoint stages, resulting in noticeable accumulated errors. In this paper, we present a neural …

Scalable, detailed and mask-free universal photometric stereo

S Ikehata - Proceedings of the IEEE/CVF Conference on …, 2023‏ - openaccess.thecvf.com
In this paper, we introduce SDM-UniPS, a groundbreaking Scalable, Detailed, Mask-free,
and Universal Photometric Stereo network. Our approach can recover astonishingly intricate …

Normattention-psn: A high-frequency region enhanced photometric stereo network with normalized attention

Y Ju, B Shi, M Jian, L Qi, J Dong, KM Lam - International Journal of …, 2022‏ - Springer
Photometric stereo aims to recover the surface normals of a 3D object from various shading
cues, establishing the relationship between two-dimensional images and the object …

Shape from polarization for complex scenes in the wild

C Lei, C Qi, J **e, N Fan, V Koltun… - Proceedings of the …, 2022‏ - openaccess.thecvf.com
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 …

DiLiGenRT: A photometric stereo dataset with quantified roughness and translucency

H Guo, J Ren, F Wang, B Shi, M Ren… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Photometric stereo faces challenges from non-Lambertian reflectance in real-world
scenarios. Systematically measuring the reliability of photometric stereo methods in …

S-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint

W Yang, G Chen, C Chen, Z Chen… - Advances in Neural …, 2022‏ - proceedings.neurips.cc
In this paper, we address the" dual problem" of multi-view scene reconstruction in which we
utilize single-view images captured under different point lights to learn a neural scene …

Deep photometric stereo for non-lambertian surfaces

G Chen, K Han, B Shi, Y Matsushita… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
This paper addresses the problem of photometric stereo, in both calibrated and uncalibrated
scenarios, for non-Lambertian surfaces based on deep learning. We first introduce a fully …

Deep 3d capture: Geometry and reflectance from sparse multi-view images

S Bi, Z Xu, K Sunkavalli, D Kriegman… - Proceedings of the …, 2020‏ - openaccess.thecvf.com
We introduce a novel learning-based method to reconstruct the high-quality geometry and
complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images …