One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer

Author:

Guo Hang1ORCID,Dai Tao2ORCID,Zhu Mingyan1ORCID,Meng Guanghao3ORCID,Chen Bin4ORCID,Wang Zhi1ORCID,Xia Shu-Tao5ORCID

Affiliation:

1. Tsinghua University, Shenzhen, China

2. Shenzhen University, Shenzhen, China

3. Tsinghua University, Peng Cheng Laboratory, Shenzhen, China

4. Harbin Institute of Technology, Shenzhen, Shenzhen, China

5. Tsinghua University & Peng Cheng Laboratory, Shenzhen, China

Funder

Shenzhen Science and Technology Program

PCNL KEY project

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

ACM

Reference62 articles.

1. Sequence-to-Sequence Contrastive Learning for Text Recognition

2. Mohamad Alansari , Oussama Abdul Hay , Sajid Javed, Abdulhaid Shoufan, Yahya Zweiri, and Naoufel Werghi. 2023 . GhostFaceNets: Lightweight Face Recognition Model from Cheap Operations. IEEE Access ( 2023). Mohamad Alansari, Oussama Abdul Hay, Sajid Javed, Abdulhaid Shoufan, Yahya Zweiri, and Naoufel Werghi. 2023. GhostFaceNets: Lightweight Face Recognition Model from Cheap Operations. IEEE Access (2023).

3. Darwin Bautista and Rowel Atienza . 2022 . Scene text recognition with permuted autoregressive sequence models. In Computer Vision--ECCV 2022: 17th European Conference , Tel Aviv , Israel, October 23-27, 2022, Proceedings, Part XXVIII. Springer, 178--196. Darwin Bautista and Rowel Atienza. 2022. Scene text recognition with permuted autoregressive sequence models. In Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXVIII. Springer, 178--196.

4. Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation

5. An approach to road scene text recognition with per-frame accumulation and dynamic stopping decision

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