A Co-Attention Method Based on Generative Adversarial Networks for Multi-view Images-Reference-Cited by-同舟云学术

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A Co-Attention Method Based on Generative Adversarial Networks for Multi-view Images

Published:2021-11-24 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)
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Author:

Huang Qi-Xian¹,Shi Shu-Pei²,Lin Guo-Shiang³,Shen Day-Fann²,Sun Hung-Min⁴

Affiliation:

1. National Tsing Hua University,Institue of Information Systems and Applications,Hsinchu,Taiwan

2. National Yunlin University of Technology,Department of Electrical Engineering,Yunlin,Taiwan

3. National Chin-Yi University of Technology,Department of Computer Science and Information Engineering,Taichung,Taiwan

4. National Tsing Hua University,Department of Computer Science,Hsinchu,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9704881/9704883/09704964.pdf?arnumber=9704964

Reference10 articles.

1. A region-based shape descriptor using Zernike moments

2. Large-scale 3D shape retrieval from ShapeNet Core55;savva;Proc Eurographics Workshop 3D Object Retrieval,2017

3. MVC

4. Multi-view Convolutional Neural Networks for 3D Shape Recognition

5. Distinctive Image Features from Scale-Invariant Keypoints

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