| --- |
| language: |
| - en |
| license: other |
| license_name: non-commercial-research-license |
| license_link: https://huggingface.co/datasets/ArtmeScienceLab/PosterIQ/blob/main/LICENSE |
| pretty_name: PosterIQ |
| tags: |
| - poster |
| - graphic-design |
| - visual-design |
| - typography |
| - layout |
| - image-generation |
| annotations_creators: |
| - expert-generated |
| - machine-generated |
| language_creators: |
| - machine-generated |
| size_categories: |
| - 1K<n<10K |
| source_datasets: |
| - original |
| task_categories: |
| - image-to-text |
| - text-to-image |
| task_ids: [] |
| configs: |
| - config_name: alignment |
| data_files: |
| - split: test |
| path: alignment/test-* |
| - config_name: composition_understanding |
| data_files: |
| - split: test |
| path: composition_understanding/test-* |
| - config_name: empty_space |
| data_files: |
| - split: test |
| path: empty_space/test-* |
| - config_name: font_attributes |
| data_files: |
| - split: test |
| path: font_attributes/test-* |
| - config_name: font_effect |
| data_files: |
| - split: test |
| path: font_effect/test-* |
| - config_name: font_effect_2 |
| data_files: |
| - split: test |
| path: font_effect_2/test-* |
| - config_name: font_matching |
| data_files: |
| - split: test |
| path: font_matching/test-* |
| - config_name: font_size_ocr |
| data_files: |
| - split: test |
| path: font_size_ocr/test-* |
| - config_name: hard_ocr |
| data_files: |
| - split: test |
| path: hard_ocr/test-* |
| - config_name: intention_understanding |
| data_files: |
| - split: test |
| path: intention_understanding/test-* |
| - config_name: layout_comparison |
| data_files: |
| - split: test |
| path: layout_comparison/test-* |
| - config_name: layout_generation |
| data_files: |
| - split: test |
| path: layout_generation/test-* |
| - config_name: logo_ocr |
| data_files: |
| - split: test |
| path: logo_ocr/test-* |
| - config_name: overall_rating |
| data_files: |
| - split: test |
| path: overall_rating/test-* |
| - config_name: poster_ocr |
| data_files: |
| - split: test |
| path: poster_ocr/test-* |
| - config_name: rotation |
| data_files: |
| - split: test |
| path: rotation/test-* |
| - config_name: simple_ocr |
| data_files: |
| - split: test |
| path: simple_ocr/test-* |
| - config_name: style_understanding |
| data_files: |
| - split: test |
| path: style_understanding/test-* |
| - config_name: text_localization |
| data_files: |
| - split: test |
| path: text_localization/test-* |
| - config_name: gen_composition |
| data_files: |
| - split: test |
| path: gen_composition/test-* |
| - config_name: gen_dense |
| data_files: |
| - split: test |
| path: gen_dense/test-* |
| - config_name: gen_font |
| data_files: |
| - split: test |
| path: gen_font/test-* |
| - config_name: gen_intention |
| data_files: |
| - split: test |
| path: gen_intention/test-* |
| - config_name: gen_style |
| data_files: |
| - split: test |
| path: gen_style/test-* |
| --- |
| |
| # Dataset Card for PosterIQ |
|
|
| [](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/ci.yaml) |
| [](https://github.com/creative-graphic-design/huggingface-datasets/actions/workflows/push_to_hub.yaml) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** https://github.com/ArtmeScienceLab/PosterIQ-Benchmark |
| - **Repository:** https://github.com/creative-graphic-design/huggingface-datasets/tree/main/datasets/PosterIQ |
| - **Hugging Face Dataset:** https://huggingface.co/datasets/creative-graphic-design/PosterIQ |
| - **Original Data:** https://huggingface.co/datasets/ArtmeScienceLab/PosterIQ |
| - **Original Code:** https://github.com/ArtmeScienceLab/PosterIQ-Benchmark |
| - **Paper (CVPR 2026 / arXiv):** https://arxiv.org/abs/2603.24078 |
| - **Leaderboard:** Not available in the original release. |
| - **Point of Contact:** https://github.com/ArtmeScienceLab/PosterIQ-Benchmark/issues |
|
|
| ### Dataset Summary |
|
|
| PosterIQ is the poster design benchmark released with *PosterIQ: A Design Perspective Benchmark for Poster Understanding and Generation*. It contains task-level evaluation data for poster understanding and poster generation from a design perspective, including typography, layout, OCR, composition, style, empty-space use, and design intention. |
|
|
| This Hugging Face loader exposes the upstream release as 24 task-level configurations. Understanding configurations include the released poster image from `data.zip`. Generation configurations contain prompts, target criteria, and task metadata; their `path` values identify intended generation output paths and do not point to released source images. |
|
|
| ### Supported Tasks and Leaderboards |
|
|
| PosterIQ is intended for evaluating vision-language and image-generation systems on poster design tasks. Understanding tasks pair an input poster image with a prompt and answer metadata. Generation tasks provide poster-generation prompts and evaluation targets or attributes for generated outputs. |
|
|
| No active public leaderboard is bundled with this Hugging Face dataset. For exact reproduction of the original evaluation scripts, use the upstream PosterIQ-Benchmark repository. |
|
|
| ### Languages |
|
|
| Prompts and annotations are primarily in English (`en`). |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| An understanding row contains task metadata, prompt text, JSON-encoded answer metadata, and an input image: |
|
|
| ```json |
| { |
| "id": "alignment-00000", |
| "task": "alignment", |
| "subtask": "", |
| "name": "000_30_center_.png", |
| "path": "alignment/000_30_center_.png", |
| "prompt": "Please observe the text alignment...", |
| "gt_json": "[\"center-aligned\"]", |
| "metadata_json": "{\"alignment\": [\"center-aligned\"]}", |
| "image": "<image>", |
| "image_path": ".../data/alignment/000_30_center_.png" |
| } |
| ``` |
|
|
| A generation row contains the prompt and metadata only: |
|
|
| ```json |
| { |
| "id": "gen_dense-00000", |
| "task": "poster dense", |
| "subtask": "", |
| "name": "1000.jpg", |
| "path": "dense/1000.jpg", |
| "prompt": "NBA Pinnacle Night...", |
| "gt_json": "[\"Aspect ratio 2:3...\"]", |
| "metadata_json": "{\"theme\": \"NBA\", \"elements\": [[\"Kevin Durant\", \"Klay Thompson\"]]}" |
| } |
| ``` |
|
|
| ### Data Fields |
|
|
| - `id` (`string`): Stable row identifier generated as `{config}-{index:05d}`. |
| - `task` (`string`): Upstream task name. |
| - `subtask` (`string`, configs where present): Upstream subtask label. |
| - `name` (`string`): Upstream file name. |
| - `path` (`string`): Upstream relative path, normalized to POSIX separators. |
| - `prompt` (`string`): Model prompt for the task. |
| - `gt_json` (`string`, only configs with `gt`): JSON-encoded upstream ground-truth field. |
| - `metadata_json` (`string`): JSON-encoded source fields not represented as standard columns. |
| - `image` (`Image`, understanding configs): Input poster image. |
| - `image_path` (`string`, understanding configs): Local resolved image path. |
| - `original_image` (`Image`, `poster_ocr` and `text_localization`): Original-resolution poster image. |
| - `original_image_path` (`string`, `poster_ocr` and `text_localization`): Local resolved original image path. |
|
|
| ### Data Splits |
|
|
| All configurations expose a single `test` split because PosterIQ is an evaluation dataset and the upstream release does not provide training partitions. |
|
|
| | Config | Split | Rows | Image | |
| | --- | --- | ---: | --- | |
| | `alignment` | test | 200 | yes | |
| | `composition_understanding` | test | 117 | yes | |
| | `empty_space` | test | 167 | yes | |
| | `font_attributes` | test | 1,813 | yes | |
| | `font_effect` | test | 450 | yes | |
| | `font_effect_2` | test | 125 | yes | |
| | `font_matching` | test | 400 | yes | |
| | `font_size_ocr` | test | 1,400 | yes | |
| | `hard_ocr` | test | 400 | yes | |
| | `intention_understanding` | test | 202 | yes | |
| | `layout_comparison` | test | 256 | yes | |
| | `layout_generation` | test | 145 | yes | |
| | `logo_ocr` | test | 600 | yes | |
| | `overall_rating` | test | 219 | yes | |
| | `poster_ocr` | test | 205 | yes | |
| | `rotation` | test | 205 | yes | |
| | `simple_ocr` | test | 400 | yes | |
| | `style_understanding` | test | 256 | yes | |
| | `text_localization` | test | 205 | yes | |
| | `gen_composition` | test | 117 | no | |
| | `gen_dense` | test | 114 | no | |
| | `gen_font` | test | 135 | no | |
| | `gen_intention` | test | 200 | no | |
| | `gen_style` | test | 256 | no | |
|
|
| ## Dataset Creation |
|
|
| ### Curation Rationale |
|
|
| PosterIQ was created to evaluate poster understanding and generation from a design perspective rather than relying only on general visual recognition or generic image-generation criteria. |
|
|
| ### Source Data |
|
|
| The upstream Hugging Face dataset provides task JSON files under `und_task/` and `gen_task/`. The `data.zip` archive contains the 7,765 images referenced by the understanding tasks. Generation tasks provide prompts and metadata for evaluating generated poster outputs. |
|
|
| ### Annotations |
|
|
| Rows contain task-specific ground truth or target metadata from the upstream release. This loader keeps task-specific fields in `metadata_json` to avoid forcing heterogeneous task schemas into a single lossy structure. |
|
|
| ### Personal and Sensitive Information |
|
|
| The dataset consists of poster images, poster-generation prompts, and design-task annotations. The dataset card does not identify personal information in the released benchmark. Posters may include names, brands, events, or culturally specific text as part of graphic design examples. |
|
|
| ## Considerations for Using the Data |
|
|
| ### Social Impact of Dataset |
|
|
| PosterIQ can support more design-aware evaluation of poster understanding and generation systems, especially typography, OCR, layout, composition, and style control. |
|
|
| ### Discussion of Biases |
|
|
| Poster design conventions, language use, typography, and style labels reflect the upstream data creation process and may not cover all cultures, domains, accessibility needs, or professional design contexts equally. |
|
|
| ### Other Known Limitations |
|
|
| Generation configurations do not include generated images in the upstream release. They provide prompts and evaluation metadata for systems that generate their own outputs. |
|
|
| ## Additional Information |
|
|
| ### Dataset Curators |
|
|
| The original PosterIQ dataset was created by Yuheng Feng, Wen Zhang, Haodong Duan, and Xingxing Zou. |
|
|
| ### Licensing Information |
|
|
| The upstream Hugging Face dataset card declares `non-commercial-research-license` with `license: other`. The upstream `LICENSE` file is empty at the time this loader was created, so users should consult the original dataset page and repository before redistribution or commercial use. |
|
|
| ### Citation Information |
|
|
| ```bibtex |
| @inproceedings{cvpr2026posteriq, |
| title={PosterIQ: A Design Perspective Benchmark for Poster Understanding and Generation}, |
| author={Feng, Yuheng and Zhang, Wen and Duan, Haodong and Zou, Xingxing}, |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
| year={2026} |
| } |
| ``` |
|
|
| ### Contributions |
|
|
| Thanks to [@ArtmeScienceLab](https://github.com/ArtmeScienceLab) for creating this dataset. |
|
|
