A dual-cue network for multispectral photometric stereo-Reference-Cited by-同舟云学术

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A dual-cue network for multispectral photometric stereo

Published:2020-04 Issue: Volume:100 Page:107162
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Ju Yakun^ORCID,Dong Xinghui^ORCID,Wang Yingyu,Qi Lin,Dong Junyu

Funder

National Key Scientific Instrument and Equipment Development Projects of China

International Science and Technology Cooperation Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference33 articles.

1. Comprehensive assessment of non-uniform illumination for 3d heightmap reconstruction in outdoor environments;Jian;Comput. Ind.,2018

2. Photometric method for determining surface orientation from multiple images;Woodham;Opt. Eng.,1980

3. Hyperspectral photometric stereo for a single capture.;Ozawa;J. Opt. Soc. Am. A,2017

4. T. Kawabata, F. Sakaue, J. Sato, One shot photometric stereo from reflectance classification, Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. (2016) 620–627.

5. H. Jiao, Y. Luo, N. Wang, L. Qi, J. Dong, H. Lei, Underwater multi-spectral photometric stereo reconstruction from a single RGBD image, Proceedings of the Signal and Information Processing Association Summit and Conference (2017) 1–4. doi:10.1109/APSIPA.2016.7820773.

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1. Efficient Feature Fusion for Learning-Based Photometric Stereo;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

2. Multispectral Photometric Stereo for Spatially-Varying Spectral Reflectances;International Journal of Computer Vision;2022-07-06

3. Improved photometric stereo based on local search;Multimedia Tools and Applications;2022-06-07

4. DiLiGenT10²: A Photometric Stereo Benchmark Dataset with Controlled Shape and Material Variation;2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2022-06

5. A deep-shallow and global–local multi-feature fusion network for photometric stereo;Image and Vision Computing;2022-02

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