Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model

Understand

TextVQA requires models to read and reason about text in images to answer questions about them.

• Specifically, models need to incorporate a new modality of text present in the images and reason over it to answer TextVQA questions.
• In this challenge, we use generative model T5 for TextVQA task.
• Based on pre-trained checkpoint T5-3B from HuggingFace repository, two other pre-training tasks including masked language modeling(MLM) and relative position prediction(RPP) are designed to better align object feature and scene text.