| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: text |
| dtype: string |
| - name: link |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 19444314153 |
| num_examples: 115818 |
| - name: validation |
| num_bytes: 4201166538 |
| num_examples: 25701 |
| - name: test |
| num_bytes: 1547637231 |
| num_examples: 9911 |
| download_size: 24003659385 |
| dataset_size: 25193117922 |
| license: apache-2.0 |
| task_categories: |
| - image-text-to-image |
| - visual-document-retrieval |
| pretty_name: SemArtPlus |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
|
|
| # Dataset Card for Dataset Name |
|
|
| SemArt+ is a multi-relational multimodal benchmark for art understanding, built by combining the original SemArt dataset with per-sentence aspect annotations from Explain Me the Painting. It contains 34,770 images of European paintings from the 3rd to 19th centuries, connected to 62,289 texts through 151,430 typed semantic edges. |
|
|
| - **Curated by:** - [Antonio Purificato](https://scholar.google.com/citations?hl=it&user=D7hppo0AAAAJ) |
| - **Language(s) (NLP):** English |
| - **License:** Apache 2.0 |
|
|
| ### Dataset Sources |
|
|
| <!-- Provide the basic links for the dataset. --> |
|
|
| - **Repository:** https://github.com/antoniopurificato/artistic_sheaf/blob/stable |
| - **Paper:** https://arxiv.org/abs/2607.16321v1 |
| |
| |
| ## Dataset Structure |
| |
| - `Image`: the image from the WikiArt dataset. |
| - `Link`: type of relation presented in the text. |
| - `Text`: Description related to the given image. |
| |
| |
| |
| ## Citation |
| |
| ``` |
| @misc{schaerf2026artsemanticssheafinformedcontrastive, |
| title={Art Beyond Semantics: Sheaf-Informed Contrastive Learning for Multi-Relational Representations}, |
| author={Ludovica Schaerf and Antonio Purificato and Piera Riccio and Fabrizio Silvestri and Noa Garcia}, |
| year={2026}, |
| eprint={2607.16321}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2607.16321}, |
| } |
| ``` |
| |
| |
| ## Dataset Card Authors [optional] |
| |
| - [Ludovica Schaerf](https://scholar.google.com/citations?user=wsURxPUAAAAJ) |
| - [Antonio Purificato](https://scholar.google.com/citations?hl=it&user=D7hppo0AAAAJ) |
| - [Piera Riccio](http://scholar.google.com/citations?user=ejhiyEIAAAAJ) |
| - [Fabrizio Silvestri](https://scholar.google.com/citations?user=pi985dQAAAAJ) |
| - [Noa Garcia](https://scholar.google.com/citations?user=m137748AAAAJ) |
| |
| ## Dataset Card Contact |
| |
| - [Antonio Purificato](https://scholar.google.com/citations?hl=it&user=D7hppo0AAAAJ) |
