[WIP] Upload CommonSketch dataset (multi-commit 4951a8295545bcce0695d5b4c5acc7eea7915688625d5fae6b4050b151062ee3)

README.md

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+---
+pretty_name: CommonSketch
+license: cc-by-4.0
+task_categories:
+- image-classification
+- image-to-text
+- visual-question-answering
+language:
+- en
+tags:
+- image
+- sketch
+- captions
+- visual-question-answering
+- commonsense
+- abstraction
+- computer-vision
+size_categories:
+- 10K<n<100K
+---
+
+# CommonSketch
+
+## Dataset Summary
+
+CommonSketch is a semantically annotated sketch dataset introduced in the paper [SEA: Evaluating Sketch Abstraction Efficiency via Element-level Commonsense Visual Question Answering](https://arxiv.org/abs/2603.28363). The dataset contains 23,100 human-drawn sketches across 300 object classes. Each sketch is paired with a fine-grained caption and element-level commonsense annotations for evaluating sketch abstraction and semantic recognizability.
+
+## Dataset Structure
+
+```text
+CommonSketch/
+  images/
+  metadata.csv
+  captions.csv
+  vqa_element_annotation.json
+  metadata/
+    classes.csv
+    classes.txt
+    commonsense_elements.json
+```
+
+## Data Fields
+
+The main row-level metadata is provided in `metadata.csv`.
+
+| Field | Description |
+| --- | --- |
+| `file_name` | Relative path to the sketch image. |
+| `caption` | Fine-grained caption describing the sketch. |
+| `class_name` | Object class name. |
+| `class_id` | Class identifier from `001` to `300`. |
+| `category` | High-level category for the class. |
+
+The `captions.csv` file provides the image-caption pairs with the following fields.
+
+| Field | Description |
+| --- | --- |
+| `image` | Image file name. |
+| `caption` | Fine-grained caption describing the sketch. |
+
+## Annotation Files
+
+`vqa_element_annotation.json` contains image-level binary element annotations. Each annotation indicates whether a class-specific commonsense element is present in the sketch.
+
+`metadata/commonsense_elements.json` defines the class-level commonsense element schema used by the VQA annotations. Each class entry includes its `class_id`, `total_elements`, and the list of element definitions.
+
+`metadata/classes.csv` provides the 300 class names, class IDs, high-level categories, and the number of commonsense elements per class. `metadata/classes.txt` provides the class list only.
+
+## Category Statistics
+
+| Category | # Classes |
+| --- | ---: |
+| animal | 61 |
+| body part | 7 |
+| clothing | 8 |
+| container | 9 |
+| electronic device | 22 |
+| food | 28 |
+| furniture | 25 |
+| icon | 13 |
+| musical instrument | 11 |
+| nature | 14 |
+| sports equipment | 14 |
+| structure | 28 |
+| tool | 37 |
+| vehicle | 23 |
+
+## Usage
+
+After upload to the Hugging Face Hub, the dataset can be loaded with:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("ziiio/CommonSketch")
+```
+
+The `file_name` field in `metadata.csv` points to the image path under `images/`.
+
+## License
+
+CommonSketch is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. If you use CommonSketch, please cite the SEA paper.
+
+## Citation
+
+```bibtex
+@article{park2026sea,
+  title={SEA: Evaluating Sketch Abstraction Efficiency via Element-level Commonsense Visual Question Answering},
+  author={Park, Jiho and Choi, Sieun and Seo, Jaeyoon and Sohn, Minho and Kim, Yeana and Kim, Jihie},
+  journal={arXiv preprint arXiv:2603.28363},
+  year={2026}
+}
+```
+
+## Links
+
+- Paper: https://arxiv.org/abs/2603.28363
+- PDF: https://arxiv.org/pdf/2603.28363
+- Code: https://github.com/zihos/SEA
+- Project page: https://zihos.github.io/SEA
+
+## Note
+
+CommonSketch includes a subset of the SketchDUO dataset. For more information about SketchDUO, please refer to https://huggingface.co/datasets/ziiio/SketchDUO.