ICDAR 2021 Competition on Scene Video Text Spotting
This work tackles the problem of spotting text in videos for applications in real-life scenarios, but it is incremental as it builds on existing image-based text spotting by extending it to video with a new dataset and competition.
The paper introduces a new competition dataset for scene video text spotting (SVTS) with 129 video clips from 21 scenarios to address the challenge of spotting text in videos due to issues like motion blur, and it reports participation from 24 teams with 46 submissions, successfully promoting research in this area.
Scene video text spotting (SVTS) is a very important research topic because of many real-life applications. However, only a little effort has 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 containts 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.