Fine-grained Pseudo Labels for Scene Text Recognition-Reference-Cited by-同舟云学术

Fine-grained Pseudo Labels for Scene Text Recognition

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Li Xiaoyu¹^ORCID,Chen Xiaoxue¹^ORCID,Huang Zuming¹^ORCID,Xie Lele¹^ORCID,Chen Jingdong¹^ORCID,Yang Ming¹^ORCID

Affiliation:

1. Ant Group, Hangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3611791

Reference59 articles.

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3. Abulikemu Abuduweili Xingjian Li Humphrey Shi Cheng-Zhong Xu and Dejing Dou. 2021. Adaptive consistency regularization for semi-supervised transfer learning. In CVPR. Abulikemu Abuduweili Xingjian Li Humphrey Shi Cheng-Zhong Xu and Dejing Dou. 2021. Adaptive consistency regularization for semi-supervised transfer learning. In CVPR.

4. Eric Arazo Diego Ortego Paul Albert Noel E O'Connor and Kevin McGuinness. 2020. Pseudo-labeling and confirmation bias in deep semi-supervised learning. In IJCNN. Eric Arazo Diego Ortego Paul Albert Noel E O'Connor and Kevin McGuinness. 2020. Pseudo-labeling and confirmation bias in deep semi-supervised learning. In IJCNN.

5. Jeonghun Baek , Geewook Kim , Junyeop Lee , Sungrae Park , Dongyoon Han , Sangdoo Yun , Seong Joon Oh, and Hwalsuk Lee . 2019 . What is wrong with scene text recognition model comparisons? dataset and model analysis. In ICCV. Jeonghun Baek, Geewook Kim, Junyeop Lee, Sungrae Park, Dongyoon Han, Sangdoo Yun, Seong Joon Oh, and Hwalsuk Lee. 2019. What is wrong with scene text recognition model comparisons? dataset and model analysis. In ICCV.