Self-attention based Text Knowledge Mining for Text Detection

Qi Wan, Haoqin Ji, Linlin Shen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Pre-trained models play an important role in deep learning based text detectors. However, most methods ignore the gap between natural images and scene text images and directly apply ImageNet for pre-training. To address such a problem, some of them firstly pre-train the model using a large amount of synthetic data and then fine-tune it on target datasets, which is task-specific and has limited generalization capability. In this paper, we focus on providing general pre-trained models for text detectors. Considering the importance of exploring text contents for text detection, we propose STKM (Self-attention based Text Knowledge Mining), which consists of a CNN Encoder and a Self-attention Decoder, to learn general prior knowledge for text detection from SynthText. Given only image level text labels, Self-attention Decoder directly decodes features extracted from CNN Encoder to texts without requirement of detection, which guides the CNN backbone to explicitly learn discriminative semantic representations ignored by previous approaches. After that, the text knowledge learned by the backbone can be transferred to various text detectors to significantly improve their detection performance (e.g., 5.89% higher F-measure for EAST on ICDAR15 dataset) without bells and whistles. Pre-trained model is available at: https://github.com/CVI-SZU/STKM.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021
PublisherIEEE Computer Society
Pages5979-5988
Number of pages10
ISBN (Electronic)9781665445092
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021 - Virtual, Online, United States
Duration: 19 Jun 202125 Jun 2021

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

Conference2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021
Country/TerritoryUnited States
CityVirtual, Online
Period19/06/2125/06/21

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Self-attention based Text Knowledge Mining for Text Detection'. Together they form a unique fingerprint.

Cite this