language:
- en
license: cc
size_categories:
- 1K<n<10K
task_categories:
- OTHER
tags:
- scientific-posters
- layout-analysis
- document-structure-analysis
SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters
This repository contains the SciPostLayoutTree dataset, introduced in the paper "SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters".
SciPostLayoutTree is a dataset of approximately 8,000 scientific posters annotated with reading order and parent-child relations. It is designed to facilitate research into structural analysis of scientific posters, which play a vital role in academic communication. The dataset specifically addresses challenges related to spatially complex relations, including upward, horizontal, and long-distance relationships, making it a valuable resource for building structure-aware interfaces.
- Paper: SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters
- Code/GitHub Repository: https://github.com/omron-sinicx/scipostlayouttree
For detailed dataset construction, experimental setup, and reproduction steps, please refer to the comprehensive instructions provided in the GitHub repository.
Sample Usage
You can visualize tree annotations using the script provided in the associated GitHub repository. First, install the necessary Python packages:
pip install opencv-python numpy matplotlib tqdm
Then, execute the visualization script:
python visualize_annotation.py
Please ensure you have completed the Dataset Construction steps outlined in the GitHub repository to prepare the data and annotation files before running the visualization.