TY  - CONF
AU  - Yipeng Sun
AU  - Zihan Ni
AU  - Chee-Kheng Chng
AU  - Yuliang Liu
AU  - Canjie Luo
AU  - Chun Chet Ng
AU  - Junyu Han
AU  - Errui Ding
AU  - Jingtuo Liu
AU  - Dimosthenis Karatzas
AU  - Chee Seng Chan
AU  - Lianwen Jin
A2  - ICDAR
PY  - 2019//
TI  - ICDAR 2019 Competition on Large-Scale Street View Text with Partial Labeling – RRC-LSVT
BT  - 15th International Conference on Document Analysis and Recognition
SP  - 1557
EP  - 1562
N2  - 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.
UR  - https://ieeexplore.ieee.org/document/8978143
L1  - http://refbase.cvc.uab.es/files/SNC2019.pdf
UR  - http://dx.doi.org/10.1109/ICDAR.2019.00250
N1  - DAG; 600.129; 600.121
ID  - Yipeng Sun2019
ER  -