Learning 3D Face Representation with Vision Transformer for Masked Face Recognition-Reference-Cited by-同舟云学术

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Learning 3D Face Representation with Vision Transformer for Masked Face Recognition

Published:2022-03 Issue: Volume: Page:
ISSN:
Container-title:2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)
language:
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Author:

Wang Yuan¹,Yang Zhen²,Zhang Zhiqiang³,Zang Huaijuan¹,Zhu Qiang⁴,Zhan Shu¹

Affiliation:

1. School of Computer and Information Hefei University of Technology,Hefei,China

2. The Second Hospital of Anhui Medical University,Hefei,China

3. Hefei University of Technology and The Second Hospital of Anhui Medical University,Hefei,China

4. Tongcheng Teachers College,Department of Commerce and Electronic Information,Tongcheng,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9852496/9852487/09852538.pdf?arnumber=9852538

Reference43 articles.

1. CosFace: Large Margin Cosine Loss for Deep Face Recognition

2. ArcFace: Additive Angular Margin Loss for Deep Face Recognition

3. Frontal to profile face verification in the wild

4. An image is worth 16×16 words: Transformers for image recognition at scale;dosovitskiy;ArXiv,2020

5. Rethinking Spatial Dimensions of Vision Transformers

Cited by 1 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. Exploring Robust Pose Invariant Face Recognition with Vision Transformers: A Multi-Modal Study;2023 IEEE 8th International Conference on Engineering Technologies and Applied Sciences (ICETAS);2023-10-25

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