The RRC-MLT-2019 report describes an expanded multi-lingual scene text challenge with new tasks, a 20k-image real dataset, synthetic data, and competition outcomes from 60 submissions.
E2E-MLT – an unconstr ained end- to-end method for multi-language scene text,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
ICDAR2019 Robust Reading Challenge on Multi-lingual Scene Text Detection and Recognition -- RRC-MLT-2019
The RRC-MLT-2019 report describes an expanded multi-lingual scene text challenge with new tasks, a 20k-image real dataset, synthetic data, and competition outcomes from 60 submissions.