README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - zh
license:
  - cc-by-sa-4.0
multilinguality: []
size_categories: []
source_datasets:
  - extended|PosterErase
task_categories:
  - other
task_ids: []
pretty_name: PKU-PosterLayout
tags:
  - layout-generation
  - graphic design
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
  - config_name: ralf-style
    data_files:
      - split: train
        path: ralf-style/train-*
      - split: validation
        path: ralf-style/validation-*
      - split: test
        path: ralf-style/test-*
      - split: no_annotation
        path: ralf-style/no_annotation-*
dataset_info:
  - config_name: default
    features:
      - name: original_poster
        dtype: image
      - name: inpainted_poster
        dtype: image
      - name: canvas
        dtype: image
      - name: basnet_saliency_map
        dtype: image
      - name: pfpn_saliency_map
        dtype: image
      - name: annotations
        sequence:
          - name: poster_path
            dtype: string
          - name: total_elem
            dtype: int32
          - name: cls_elem
            dtype:
              class_label:
                names:
                  '0': text
                  '1': logo
                  '2': underlay
                  '3': INVALID
          - name: box_elem
            sequence: int32
    splits:
      - name: train
        num_bytes: 7146183585.374
        num_examples: 9974
      - name: test
        num_bytes: 366746518
        num_examples: 905
    download_size: 0
    dataset_size: 7512930103.374
  - config_name: ralf-style
    features:
      - name: image_id
        dtype: int32
      - name: original_poster
        dtype: image
      - name: inpainted_poster
        dtype: image
      - name: canvas
        dtype: image
      - name: saliency_map
        dtype: image
      - name: saliency_map_sub
        dtype: image
      - name: annotations
        sequence:
          - name: poster_path
            dtype: string
          - name: total_elem
            dtype: int32
          - name: cls_elem
            dtype:
              class_label:
                names:
                  '0': text
                  '1': logo
                  '2': underlay
                  '3': INVALID
          - name: box_elem
            sequence: int32
    splits:
      - name: train
        num_bytes: 4906719583.266662
        num_examples: 7979
      - name: validation
        num_bytes: 611599848.3553238
        num_examples: 997
      - name: test
        num_bytes: 613209339.4670142
        num_examples: 998
      - name: no_annotation
        num_bytes: 346581773
        num_examples: 905
    download_size: 6463429980
    dataset_size: 6478110544.089

Dataset Card for PKU-PosterLayout

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: http://59.108.48.34/tiki/PosterLayout/
• Repository: https://github.com/shunk031/huggingface-datasets_PKU-PosterLayout
• Paper (Preprint): https://arxiv.org/abs/2303.15937
• Paper (CVPR2023): https://openaccess.thecvf.com/content/CVPR2023/html/Hsu_PosterLayout_A_New_Benchmark_and_Approach_for_Content-Aware_Visual-Textual_Presentation_CVPR_2023_paper.html

Dataset Summary

PKU-PosterLayout is a new dataset and benchmark for content-aware visual-textual presentation layout.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

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

Dataset Structure

Data Instances

import datasets as ds

dataset = ds.load_dataset("creative-graphic-design/PKU-PosterLayout")

# or you can download RALF (https://arxiv.org/abs/2311.13602)-style preprocessed dataset
dataset = ds.load_dataset("creative-graphic-design/PKU-PosterLayout", name="ralf-style")

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

[More Information Needed]

Citation Information

@inproceedings{hsu2023posterlayout,
  title={PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout},
  author={Hsu, Hsiao Yuan and He, Xiangteng and Peng, Yuxin and Kong, Hao and Zhang, Qing},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={6018--6026},
  year={2023}
}

Contributions

Thanks to @PKU-ICST-MIPL for creating this dataset.