annotations_creators | language | language_creators | license | multilinguality | pretty_name | size_categories | source_datasets | tags | task_categories | task_ids | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
PKU-PosterLayout |
|
|
|
- Dataset Card Creation Guide
- 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
PKU-PosterLayout is a new dataset and benchmark for content-aware visual-textual presentation layout.
[More Information Needed]
The language data in PKU-PosterLayout is in Chinese (BCP-47 zh).
To use PKU-PosterLayout dataset, you need to download the poster image and saliency maps via PKU Netdisk or Google Drive.
/path/to/datasets
├── train
│ ├── inpainted_poster.zip
│ ├── original_poster.zip
│ ├── saliencymaps_basnet.zip
│ └── saliencymaps_pfpn.zip
└── test
├── image_canvas.zip
├── saliencymaps_basnet.zip
└── saliencymaps_pfpn.zip
import datasets as ds
dataset = ds.load_dataset(
path="shunk031/PKU-PosterLayout",
data_dir="/path/to/datasets/",
)
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
[More Information Needed]
@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}
}
Thanks to @PKU-ICST-MIPL for creating this dataset.