Gloss Prior Guided Visual Feature Learning for Continuous Sign Language Recognition-Reference-Cited by-同舟云学术

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Gloss Prior Guided Visual Feature Learning for Continuous Sign Language Recognition

Published:2024 Issue: Volume:33 Page:3486-3495
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Guo Leming¹^ORCID,Xue Wanli¹^ORCID,Liu Bo²,Zhang Kaihua³^ORCID,Yuan Tiantian¹^ORCID,Metaxas Dimitris⁴

Affiliation:

1. School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China

2. Walmart Global Tech, Sunnyvale, CA, USA

3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

4. Department of Computer Science, Rutgers University, Piscataway, NJ, USA

Funder

National Natural Science Foundation of China

Tianjin Research Innovation Project for Postgraduate Students

Tianjin Municipal Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/83/10346232/10542663.pdf?arnumber=10542663

Reference45 articles.

1. Distilling Cross-Temporal Contexts for Continuous Sign Language Recognition

2. Neural Sign Language Translation

3. Stochastic Fine-Grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition

4. Visual Alignment Constraint for Continuous Sign Language Recognition

5. Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos

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