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A Transformer-Based Decoupled Attention Network for Text Recognition in Shopping Receipt Images

  • Lang Ren
  • , Haibin Zhou
  • , Jiaqi Chen
  • , Lujiao Shao
  • , Yingji Wu
  • , Haijun Zhang*
  • *Corresponding author for this work

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

Abstract

Optical character recognition (OCR) of shopping receipts plays an important role in smart business and personal financial management. Many challenging issues remain in current OCR systems for text recognition of shopping receipts captured by mobile phones. This research constructs a multi-task model by integrating saliency object detection as a branch task, which enables us to filter out irrelevant text instances by detecting the outline of a shopping receipt. Moreover, the developed model utilized a deformable convolution so as to learning visual information more effectively. On the other hand, to deal with attention drift of text recognition, we propose a transformer-based decoupled attention network, which is able to decouple the attention and prediction processes in attention mechanism. This mechanism can not only increase prediction accuracy, but also increase the inference speed. Extensive experimental results on a large-scale real-life dataset exhibit the effectiveness of our proposed method.

Original languageEnglish
Title of host publicationNeural Computing for Advanced Applications - Second International Conference, NCAA 2021, Proceedings
EditorsHaijun Zhang, Zhi Yang, Zhao Zhang, Zhou Wu, Tianyong Hao
PublisherSpringer Science and Business Media Deutschland GmbH
Pages563-577
Number of pages15
ISBN (Print)9789811651878
DOIs
StatePublished - 2021
Externally publishedYes
Event2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021 - Guangzhou, China
Duration: 27 Aug 202130 Aug 2021

Publication series

NameCommunications in Computer and Information Science
Volume1449
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021
Country/TerritoryChina
CityGuangzhou
Period27/08/2130/08/21

Keywords

  • Optical character recognition
  • Saliency object detection
  • Shopping receipt
  • Text detection
  • Text recognition

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