MVSNet++: Learning Depth-Based Attention Pyramid Features for Multi-View Stereo-Reference-Cited by-同舟云学术

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MVSNet++: Learning Depth-Based Attention Pyramid Features for Multi-View Stereo

Published:2020 Issue: Volume:29 Page:7261-7273
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Chen Po-Heng^ORCID,Yang Hsiao-Chien^ORCID,Chen Kuan-Wen^ORCID,Chen Yong-Sheng^ORCID

Funder

Ministry of Science and Technology of Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/8835130/09115828.pdf?arnumber=9115828

Cited by 32 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced feature pyramid for multi-view stereo with adaptive correlation cost volume;Applied Intelligence;2024-06-15

2. Attention-enhanced multi-source cost volume multi-view stereo;Engineering Applications of Artificial Intelligence;2024-06

3. Cayley Rotation Averaging: Multiple Camera Averaging Under the Cayley Framework;IEEE Transactions on Image Processing;2024

4. EI-MVSNet: Epipolar-Guided Multi-View Stereo Network With Interval-Aware Label;IEEE Transactions on Image Processing;2024

5. Exploring the Point Feature Relation on Point Cloud for Multi-View Stereo;IEEE Transactions on Circuits and Systems for Video Technology;2023-11

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