Multistage Pixel-Visibility Learning With Cost Regularization for Multiview Stereo-Reference-Cited by-同舟云学术

Multistage Pixel-Visibility Learning With Cost Regularization for Multiview Stereo

Published:2023-04 Issue:2 Volume:20 Page:751-762
ISSN:1545-5955
Container-title:IEEE Transactions on Automation Science and Engineering
language:
Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Guan Xiaorong¹^ORCID,Tong Wei¹^ORCID,Jiang Shan²^ORCID,Sun Poly Z. H.³^ORCID,Wu Edmond Q.⁴^ORCID,Chen Guimin⁵

Affiliation:

1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

2. Johnson & Johnson Supply Chain, Bridgewater Township, NJ, USA

3. Department of Industrial Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

4. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

5. State Key Laboratory of Manufacturing Systems Engineering and the Shaanxi Key Laboratory of Intelligent Robots, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China

Funder

National Defense Basic Scientific Research Program of China

National Natural Science Foundation of China through the Main Research Project on Machine Behavior and Human–Machine Collaborated Decision Making Methodology

Third Research Project on Human Behavior in Human–Machine Collaboration

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8856/10094220/09761790.pdf?arnumber=9761790

Reference40 articles.

1. Large Scale Multi-view Stereopsis Evaluation

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3. Tanks and temples

4. Deep Stereo Using Adaptive Thin Volume Representation With Uncertainty Awareness

5. MVSNet: Depth inference for unstructured multi-view stereo;yao;Proc Eur Conf Comput Vis (ECCV),2018

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