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HRRegionNet: Chinese Character Segmentation in Historical Documents with Regional Awareness Read chapter Read first chapter

2021 | OriginalPaper | Chapter

ICDAR 2021 Competition on Scene Video Text Spotting

Authors : Zhanzhan Cheng, Jing Lu, Baorui Zou, Shuigeng Zhou, Fei Wu

Published in: Document Analysis and Recognition – ICDAR 2021

Publisher: Springer International Publishing

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Abstract

Scene video text spotting (SVTS) is a very important research topic because of many real-life applications. However, only a little effort has been put to spotting scene video text, in contrast to massive studies of scene text spotting in static images. Due to various environmental interferences like motion blur, spotting scene video text becomes very challenging. To promote this research area, this competition introduces a new challenge dataset containing 129 video clips from 21 natural scenarios in full annotations. The competition contains three tasks, that is, video text detection (Task 1), video text tracking (Task 2) and end-to-end video text spotting (Task3). During the competition period (opened on 1st March, 2021 and closed on 11th April, 2021), a total of 24 teams participated in the three proposed tasks with 46 valid submissions, respectively. This paper includes dataset descriptions, task definitions, evaluation protocols and results summaries of the ICDAR 2021 on SVTS competition. Thanks to the healthy number of teams as well as submissions, we consider that the SVTS competition has been successfully held, drawing much attention from the community and promoting the field research and its development.

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Footnotes
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Metadata
Title
ICDAR 2021 Competition on Scene Video Text Spotting
Authors
Zhanzhan Cheng
Jing Lu
Baorui Zou
Shuigeng Zhou
Fei Wu
Copyright Year
2021
Book
Document Analysis and Recognition – ICDAR 2021

Print ISBN: 978-3-030-86336-4

Electronic ISBN: 978-3-030-86337-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-86337-1_43

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