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--- |
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license: mit |
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task_categories: |
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- visual-question-answering |
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- image-classification |
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language: |
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- en |
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tags: |
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- visual reason |
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- transformation |
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- benchmark |
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- computer vision |
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size_categories: |
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- 1K<n<10K |
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--- |
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# VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning |
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[](http://arxiv.org/abs/2508.04043) |
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## Dataset Description |
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VisualTrans is the first comprehensive benchmark specifically designed for Visual Transformation Reasoning (VTR) in real-world human-object interaction scenarios. The benchmark encompasses 12 semantically diverse manipulation tasks and systematically evaluates three essential reasoning dimensions through 6 well-defined subtask types. |
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## Dataset Statistics |
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- **Total samples**: 497 |
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- **Number of manipulation scenarios**: 12 |
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- **Task types**: 6 |
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### Task Type Distribution |
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- **count**: 63 samples (12.7%) |
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- **procedural_causal**: 86 samples (17.3%) |
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- **procedural_interm**: 88 samples (17.7%) |
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- **procedural_plan**: 42 samples (8.5%) |
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- **spatial_fine_grained**: 168 samples (33.8%) |
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- **spatial_global**: 50 samples (10.1%) |
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### Manipulation Scenarios |
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The benchmark covers 12 diverse manipulation scenarios: |
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- Add Remove Lid |
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- Assemble Disassemble Legos |
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- Build Unstack Lego |
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- Insert Remove Bookshelf |
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- Insert Remove Cups From Rack |
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- Make Sandwich |
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- Pick Place Food |
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- Play Reset Connect Four |
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- Screw Unscrew Fingers Fixture |
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- Setup Cleanup Table |
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- Sort Beads |
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- Stack Unstack Bowls |
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## Dataset Structure |
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### Files |
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- `VisualTrans.json`: Main benchmark file containing questions, answers, and image paths |
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- `images.zip`: Compressed archive containing all images used in the benchmark |
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### Data Format |
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Each sample in the benchmark contains: |
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```json |
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{ |
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"task_type": "what", |
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"images": [ |
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"scene_name/image1.jpg", |
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"scene_name/image2.jpg" |
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], |
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"scene": "scene_name", |
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"question": "Question about the transformation", |
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"label": "Ground truth answer" |
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} |
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``` |
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## Reasoning Dimensions |
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The framework evaluates three essential reasoning dimensions: |
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1. **Quantitative Reasoning** - Counting and numerical reasoning tasks |
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2. **Procedural Reasoning** |
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- **Intermediate State** - Understanding process states during transformation |
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- **Causal Reasoning** - Analyzing cause-effect relationships |
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- **Transformation Planning** - Multi-step planning and sequence reasoning |
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3. **Spatial Reasoning** |
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- **Fine-grained** - Precise spatial relationships and object positioning |
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- **Global** - Overall spatial configuration and scene understanding |
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## Usage |
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```python |
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import json |
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import zipfile |
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# Load the benchmark data |
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with open('VisualTrans.json', 'r') as f: |
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benchmark_data = json.load(f) |
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# Extract images |
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with zipfile.ZipFile('images.zip', 'r') as zip_ref: |
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zip_ref.extractall('images/') |
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# Access a sample |
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sample = benchmark_data[0] |
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print(f"Question: {sample['question']}") |
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print(f"Answer: {sample['label']}") |
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print(f"Images: {sample['images']}") |
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``` |
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## Citation |
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If you use this benchmark, please cite our work: |
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```bibtex |
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@misc{ji2025visualtransbenchmarkrealworldvisual, |
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title={VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning}, |
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author={Yuheng Ji and Yipu Wang and Yuyang Liu and Xiaoshuai Hao and Yue Liu and Yuting Zhao and Huaihai Lyu and Xiaolong Zheng}, |
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year={2025}, |
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eprint={2508.04043}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2508.04043}, |
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} |
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``` |
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## License |
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This dataset is released under the MIT License. |
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## Contact |
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For questions or issues, please open an issue on our [GitHub repository](https://github.com/WangYipu2002/VisualTrans) or contact the authors. |
