Separate and Locate: Rethink the Text in Text-based Visual Question Answering

1 code implementation • 31 Aug 2023 • Chengyang Fang, Jiangnan Li, Liang Li, Can Ma, Dayong Hu

To tackle these problems, we propose a novel method named Separate and Locate (SaL) that explores text contextual cues and designs spatial position embedding to construct spatial relations between OCR texts.

Optical Character Recognition (OCR) Position +3

CATS: A Pragmatic Chinese Answer-to-Sequence Dataset with Large Scale and High Quality

no code implementations • 20 Jun 2023 • Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Rongyu Cao, Binhua Li, Fei Huang, Yongbin Li

To alleviate these limitations, in this paper, we present CATS, a pragmatic Chinese answer-to-sequence dataset with large scale and high quality.

Plan-then-Seam: Towards Efficient Table-to-Text Generation

1 code implementation • 10 Feb 2023 • Liang Li, Ruiying Geng, Chengyang Fang, Bing Li, Can Ma, Binhua Li, Yongbin Li

Table-to-text generation aims at automatically generating text to help people conveniently obtain salient information in tables.

Table-to-Text Generation

Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering

no code implementations • 24 Mar 2022 • Chengyang Fang, Gangyan Zeng, Yu Zhou, Daiqing Wu, Can Ma, Dayong Hu, Weiping Wang

Texts in scene images convey critical information for scene understanding and reasoning.

Optical Character Recognition Optical Character Recognition (OCR) +3