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original_poster
image
inpainted_poster
image
basnet_saliency_map
image
pfpn_saliency_map
image
canvas
image
annotations
sequence
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{ "poster_path": [ "train/1.png", "train/1.png", "train/1.png", "train/1.png" ], "total_elem": [ 4, 4, 4, 4 ], "cls_elem": [ 0, 0, 2, 0 ], "box_elem": [ [ 411, 144, 498, 168 ], [ 214, 185, 501, 215 ...
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{ "poster_path": [ "train/2.png", "train/2.png", "train/2.png" ], "total_elem": [ 3, 3, 3 ], "cls_elem": [ 0, 0, 0 ], "box_elem": [ [ 35, 599, 462, 640 ], [ 297, 668, 462, 706 ], [ 31, 670, ...
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{ "poster_path": [ "train/3.png", "train/3.png", "train/3.png", "train/3.png", "train/3.png" ], "total_elem": [ 5, 5, 5, 5, 5 ], "cls_elem": [ 0, 2, 2, 0, 0 ], "box_elem": [ [ 46, 482, 466, 542 ], [ 50, ...
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{ "poster_path": [ "train/4.png", "train/4.png", "train/4.png", "train/4.png", "train/4.png" ], "total_elem": [ 5, 5, 5, 5, 5 ], "cls_elem": [ 1, 0, 0, 2, 0 ], "box_elem": [ [ 150, 30, 350, 80 ], [ 450, ...
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{ "poster_path": [ "train/6.png", "train/6.png", "train/6.png", "train/6.png", "train/6.png" ], "total_elem": [ 5, 5, 5, 5, 5 ], "cls_elem": [ 0, 2, 0, 2, 0 ], "box_elem": [ [ 375, 474, 454, 503 ], [ 45, ...
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{ "poster_path": [ "train/8.png", "train/8.png", "train/8.png" ], "total_elem": [ 3, 3, 3 ], "cls_elem": [ 1, 2, 0 ], "box_elem": [ [ 70, 43, 442, 67 ], [ 30, 100, 490, 175 ], [ 95, 122, ...
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{ "poster_path": [ "train/30.png", "train/30.png", "train/30.png" ], "total_elem": [ 3, 3, 3 ], "cls_elem": [ 0, 2, 0 ], "box_elem": [ [ 63, 139, 448, 191 ], [ 130, 210, 383, 245 ], [ 174, 2...
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{ "poster_path": [ "train/88.png", "train/88.png", "train/88.png", "train/88.png", "train/88.png", "train/88.png" ], "total_elem": [ 6, 6, 6, 6, 6, 6 ], "cls_elem": [ 1, 0, 0, 0, 2, 0 ], "box_elem": [ [ 125, 37, ...
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{ "poster_path": [ "train/98.png", "train/98.png", "train/98.png" ], "total_elem": [ 3, 3, 3 ], "cls_elem": [ 0, 2, 0 ], "box_elem": [ [ 48, 492, 478, 566 ], [ 53, 591, 462, 639 ], [ 105, 59...
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Dataset Card for PKU-PosterLayout

CI

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.

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