ICDAR2017 Robust Reading Challenge on COCO-Text

Publikation: Bidrag til tidsskriftKonferenceartikelForskningfagfællebedømt

  • Raul Gomez
  • Baoguang Shi
  • Lluis Gomez
  • Lukas Numann
  • Andreas Veit
  • Jiri Matas
  • Belongie, Serge
  • Dismosthenis Karatzas

This report presents the final results of the ICDAR 2017 Robust Reading Challenge on COCO-Text. A challenge on scene text detection and recognition based on the largest real scene text dataset currently available: the COCO-Text dataset. The competition is structured around three tasks: Text Localization, Cropped Word Recognition and End-To-End Recognition. The competition received a total of 27 submissions over the different opened tasks. This report describes the datasets and the ground truth, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.

OriginalsprogEngelsk
TidsskriftProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Sider (fra-til)1435-1443
Antal sider9
ISSN1520-5363
DOI
StatusUdgivet - 25 jan. 2018
Eksternt udgivetJa
Begivenhed14th IAPR International Conference on Document Analysis and Recognition, ICDAR 2017 - Kyoto, Japan
Varighed: 9 nov. 201715 nov. 2017

Konference

Konference14th IAPR International Conference on Document Analysis and Recognition, ICDAR 2017
LandJapan
ByKyoto
Periode09/11/201715/11/2017
Sponsoret al., FxPaL, Glory, Hitachi, Media Drive, Sansan

Bibliografisk note

Publisher Copyright:
© 2017 IEEE.

ID: 301826271