Generating Questions via Unexploited OCR Texts: Prompt-Based Data Augmentation for TextVQA-Reference-Cited by-同舟云学术

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Generating Questions via Unexploited OCR Texts: Prompt-Based Data Augmentation for TextVQA

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
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Author:

Han Mingjie¹,Jin Ting¹,Lin Wancong¹,Li Can²,Qiao Liang³

Affiliation:

1. School of Computer Science and Technology, Hainan University,HaiKou,China

2. School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University,Shanghai,China

3. School of Computer Science and Technology, Zhejiang University,Hangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191606.pdf?arnumber=10191606

Reference35 articles.

1. LSTM: A Search Space Odyssey

2. Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps

3. Microsoft coco: Common objects in context;lin;Computer Vision-ECCV 2014 13th European Conference,2014

4. Cascade Reasoning Network for Text-based Visual Question Answering

5. Visual Question Generation as Dual Task of Visual Question Answering

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. Prompt Tuning Models on Sentiment-Aware for Explainable Recommendation;Lecture Notes in Computer Science;2024

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