ICDAR2017 Robust Reading Challenge on COCO-Text

Publikation: Bidrag til tidsskriftKonferenceartikelForskningfagfællebedømt

  • Belongie, Serge
  • Raúl Gómez
  • Baoguang Shi
  • Lluis Gomez-Pujol
  • Lukas Neumann
  • Andreas Veit
  • Jiri Matas
  • Dimosthenis 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
TidsskriftIEEE Xplore Digital Library
Antal sider9
DOI
StatusUdgivet - 29 jan. 2018
Eksternt udgivetJa

ID: 307526853