InfographicVQA
Author:
Affiliation:
1. IIIT Hyderabad,CVIT,India
2. IISER Pune,India
3. UAB,Computer Vision Center,Spain
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9706406/9706408/09706887.pdf?arnumber=9706887
Reference50 articles.
1. Towards VQA Models That Can Read
2. Are we pretraining it right? Digging deeper into visio-linguistic pretraining;singh,2020
3. Pytorch: An imperative style, high-performance deep learning library;paszke;NeurIPS,2019
4. OCR-VQA: Visual Question Answering by Reading Text in Images
5. DocVQA: A Dataset for VQA on Document Images;mathew;WACV,2020
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