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Author Yipeng Sun; Zihan Ni; Chee-Kheng Chng; Yuliang Liu; Canjie Luo; Chun Chet Ng; Junyu Han; Errui Ding; Jingtuo Liu; Dimosthenis Karatzas; Chee Seng Chan; Lianwen Jin edit   pdf
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  Title ICDAR 2019 Competition on Large-Scale Street View Text with Partial Labeling – RRC-LSVT Type Conference Article
  Year 2019 Publication 15th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1557-1562  
  Keywords  
  Abstract Robust text reading from street view images provides valuable information for various applications. Performance improvement of existing methods in such a challenging scenario heavily relies on the amount of fully annotated training data, which is costly and in-efficient to obtain. To scale up the amount of training data while keeping the labeling procedure cost-effective, this competition introduces a new challenge on Large-scale Street View Text with Partial Labeling (LSVT), providing 50, 000 and 400, 000 images in full and weak annotations, respectively. This competition aims to explore the abilities of state-of-the-art methods to detect and recognize text instances from large-scale street view images, closing the gap between research benchmarks and real applications. During the competition period, a total of 41 teams participated in the two proposed tasks with 132 valid submissions, ie, text detection and end-to-end text spotting. This paper includes dataset descriptions, task definitions, evaluation protocols and results summaries of the ICDAR 2019-LSVT challenge.  
  Address Sydney; Australia; September 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume (down) Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.129; 600.121 Approved no  
  Call Number Admin @ si @ SNC2019 Serial 3339  
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