ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)

@article{Shi2017ICDAR2017CO,
  title={ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)},
  author={Baoguang Shi and Cong Yao and Minghui Liao and Mingkun Yang and P. Xu and L. Cui and Serge J. Belongie and S. Lu and X. Bai},
  journal={2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)},
  year={2017},
  volume={01},
  pages={1429-1434}
}
  • Baoguang Shi, Cong Yao, +6 authors X. Bai
  • Published 2017
  • Computer Science
  • 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)
  • Chinese is the most widely used language in the world. Algorithms that read Chinese text in natural images facilitate applications of various kinds. Despite the large potential value, datasets and competitions in the past primarily focus on English, which bares very different characteristics than Chinese. This report introduces RCTW, a new competition that focuses on Chinese text reading. The competition features a large-scale dataset with over 12,000 annotated images. Two tasks, namely text… CONTINUE READING
    66 Citations

    Figures, Tables, and Topics from this paper

    Explore Further: Topics Discussed in This Paper

    ICDAR 2019 Competition on Large-Scale Street View Text with Partial Labeling - RRC-LSVT
    • Y. Sun, Zihan Ni, +9 authors Lianwen Jin
    • Computer Science
    • 2019 International Conference on Document Analysis and Recognition (ICDAR)
    • 2019
    • 7
    • PDF
    Chinese Street View Text: Large-Scale Chinese Text Reading With Partially Supervised Learning
    • 11
    • Highly Influenced
    • PDF
    A Large Chinese Text Dataset in the Wild
    • 9
    • Highly Influenced
    • PDF
    ICPR2018 Contest on Robust Reading for Multi-Type Web Images
    • 10
    ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text - RRC-ArT
    • 14
    • Highly Influenced
    • PDF
    Multi-scene ancient chinese text recognition
    N-FTRN: Neighborhoods based fully convolutional network for Chinese text line recognition
    • 1
    Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps
    • PDF
    ShopSign: a Diverse Scene Text Dataset of Chinese Shop Signs in Street Views
    • Highly Influenced
    • PDF
    Structured Multimodal Attentions for TextVQA
    • 3
    • PDF

    References

    SHOWING 1-10 OF 10 REFERENCES
    ICDAR 2015 competition on Robust Reading
    • 535
    • PDF
    ICDAR 2013 Robust Reading Competition
    • 699
    • PDF
    Detecting Oriented Text in Natural Images by Linking Segments
    • 328
    • PDF
    Detecting texts of arbitrary orientations in natural images
    • 530
    • PDF
    Word Spotting in the Wild
    • 378
    • PDF
    An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition
    • 909
    • PDF
    Deep Direct Regression for Multi-oriented Scene Text Detection
    • 210
    • PDF
    Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
    • 21,090
    • PDF
    The Pascal Visual Object Classes (VOC) Challenge
    • 8,825
    • PDF
    Synthetic Data for Text Localisation in Natural Images
    • 613
    • PDF