Structured text extraction is one of the most valuable and challenging
application directions in the field of Document AI. However, the scenarios of
past benchmarks are limited, and the corresponding evaluation protocols usually
focus on the submodules of the structured text extraction scheme. In order to
eliminate these problems, we organized the ICDAR 2023 competition on Structured
text extraction from Visually-Rich Document images (SVRD). We set up two tracks
for SVRD including Track 1: HUST-CELL and Track 2: Baidu-FEST, where HUST-CELL
aims to evaluate the end-to-end performance of Complex Entity Linking and
Labeling, and Baidu-FEST focuses on evaluating the performance and
generalization of Zero-shot / Few-shot Structured Text extraction from an
end-to-end perspective. Compared to the current document benchmarks, our two
tracks of competition benchmark enriches the scenarios greatly and contains
more than 50 types of visually-rich document images (mainly from the actual
enterprise applications). The competition opened on 30th December, 2022 and
closed on 24th March, 2023. There are 35 participants and 91 valid submissions
received for Track 1, and 15 participants and 26 valid submissions received for
Track 2. In this report we will presents the motivation, competition datasets,
task definition, evaluation protocol, and submission summaries. According to
the performance of the submissions, we believe there is still a large gap on
the expected information extraction performance for complex and zero-shot
scenarios. It is hoped that this competition will attract many researchers in
the field of CV and NLP, and bring some new thoughts to the field of Document
AI.

ICDAR 2023 competition on Structured text extraction from Visually-Rich Document images (SVRD) organized with two tracks for evaluating end-to-end Complex Entity Linking and Labeling and Zero-shot / Few-shot Structured Text extraction respectively, with more than 50 types of visually-rich document images from enterprise applications, attracting 35 and 15 participants respectively and revealing a large gap in expected information extraction performance for complex and zero-shot scenarios.

ICDAR 2023 结构化文本提取竞赛之视觉丰富文档图像

ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich  Document Images

Reading seal title text is a challenging task due to the variable shapes of
seals, curved text, background noise, and overlapped text. However, this
important element is commonly found in official and financial scenarios, and
has not received the attention it deserves in the field of OCR technology. To
promote research in this area, we organized ICDAR 2023 competition on reading
the seal title (ReST), which included two tasks: seal title text detection
(Task 1) and end-to-end seal title recognition (Task 2). We constructed a
dataset of 10,000 real seal data, covering the most common classes of seals,
and labeled all seal title texts with text polygons and text contents. The
competition opened on 30th December, 2022 and closed on 20th March, 2023. The
competition attracted 53 participants from academia and industry including 28
submissions for Task 1 and 25 submissions for Task 2, which demonstrated
significant interest in this challenging task. In this report, we present an
overview of the competition, including the organization, challenges, and
results. We describe the dataset and tasks, and summarize the submissions and
evaluation results. The results show that significant progress has been made in
the field of seal title text reading, and we hope that this competition will
inspire further research and development in this important area of OCR
technology.

本文介绍了 ICDAR 2023 印章标题文本识别（ReST）比赛，并概述了比赛的组织、挑战和结果，报道了来自学术界和工业界的 53 位参与者，包括 28 个 Task 1 的提交和 25 个 Task 2 的提交，结果表明印章标题文本识别领域已取得了重要进展，激励了进一步的研究和发展。