README.md

metadata

annotations_creators:
  - machine-generated
language:
  - zh
language_creators:
  - found
license:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
pretty_name: PosterErase
size_categories: []
source_datasets:
  - original
tags:
  - graphic design
task_categories:
  - other
task_ids: []

Dataset Card for PosterErase

Table of Contents

• Dataset Card Creation Guide
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
    • Annotations
      • Annotation process
      • Who are the annotators?
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information
    • Contributions

Dataset Description

• Homepage: https://github.com/alimama-creative/Self-supervised-Text-Erasing
• Repository: https://github.com/shunk031/huggingface-datasets_PosterErase
• Paper (Preprint): https://arxiv.org/abs/2204.12743
• Paper (ACMMM2022): https://dl.acm.org/doi/abs/10.1145/3503161.3547905

Dataset Summary

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The language data in PKU-PosterLayout is in Chinese (BCP-47 zh).

Dataset Structure

Data Instances

To use PosterErase dataset, you need to download the dataset via Alibaba Cloud. Then place the downloaded files in the following structure and specify its path.

/path/to/datasets
├── erase_1.zip
├── erase_2.zip
├── erase_3.zip
├── erase_4.zip
├── erase_5.zip
└── erase_6.zip

import datasets as ds

dataset = ds.load_dataset(
    path="shunk031/PosterErase",
    data_dir="/path/to/datasets/",
)

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

You can find the following statement in the license section of the dataset distribution location.

The dataset is distributed under the CC BY-SA 4.0 license.

However, the license setting on that page appears to be set to CC-BY-SA-NC 4.0.

Citation Information

@inproceedings{jiang2022self,
  title={Self-supervised text erasing with controllable image synthesis},
  author={Jiang, Gangwei and Wang, Shiyao and Ge, Tiezheng and Jiang, Yuning and Wei, Ying and Lian, Defu},
  booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
  pages={1973--1983},
  year={2022}
}

Contributions

Thanks to alimama-creative for creating this dataset.