Upload 数据集说明文档

README.md

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+---
+license: mit
+task_categories:
+- visual-question-answering
+- image-classification
+language:
+- en
+tags:
+- visual-reasoning
+- transformation
+- benchmark
+- computer-vision
+size_categories:
+- 1K<n<10K
+---
+
+# VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning
+
+[![arXiv](https://img.shields.io/badge/arXiv-2508.04043-b31b1b.svg)](http://arxiv.org/abs/2508.04043)
+
+## Dataset Description
+
+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.
+
+## Dataset Statistics
+
+- **Total samples**: 497
+- **Number of manipulation scenarios**: 12
+- **Task types**: 6
+
+### Task Type Distribution
+
+- **count**: 63 samples (12.7%)
+- **procedural_causal**: 86 samples (17.3%)
+- **procedural_interm**: 88 samples (17.7%)
+- **procedural_plan**: 42 samples (8.5%)
+- **spatial_fine_grained**: 168 samples (33.8%)
+- **spatial_global**: 50 samples (10.1%)
+
+
+### Manipulation Scenarios
+
+The benchmark covers 12 diverse manipulation scenarios:
+- Add Remove Lid
+- Assemble Disassemble Legos
+- Build Unstack Lego
+- Insert Remove Bookshelf
+- Insert Remove Cups From Rack
+- Make Sandwich
+- Pick Place Food
+- Play Reset Connect Four
+- Screw Unscrew Fingers Fixture
+- Setup Cleanup Table
+- Sort Beads
+- Stack Unstack Bowls
+
+
+## Dataset Structure
+
+### Files
+
+- `VisualTrans.json`: Main benchmark file containing questions, answers, and image paths
+- `images.zip`: Compressed archive containing all images used in the benchmark
+
+### Data Format
+
+Each sample in the benchmark contains:
+
+```json
+{
+    "task_type": "what",
+    "images": [
+        "scene_name/image1.jpg",
+        "scene_name/image2.jpg"
+    ],
+    "scene": "scene_name",
+    "question": "Question about the transformation",
+    "label": "Ground truth answer"
+}
+```
+
+## Reasoning Dimensions
+
+The framework evaluates three essential reasoning dimensions:
+
+1. **Quantitative Reasoning** - Counting and numerical reasoning tasks
+2. **Procedural Reasoning**
+   - **Intermediate State** - Understanding process states during transformation
+   - **Causal Reasoning** - Analyzing cause-effect relationships
+   - **Transformation Planning** - Multi-step planning and sequence reasoning
+3. **Spatial Reasoning**
+   - **Fine-grained** - Precise spatial relationships and object positioning
+   - **Global** - Overall spatial configuration and scene understanding
+
+## Usage
+
+```python
+import json
+import zipfile
+
+# Load the benchmark data
+with open('VisualTrans.json', 'r') as f:
+    benchmark_data = json.load(f)
+
+# Extract images
+with zipfile.ZipFile('images.zip', 'r') as zip_ref:
+    zip_ref.extractall('images/')
+
+# Access a sample
+sample = benchmark_data[0]
+print(f"Question: {sample['question']}")
+print(f"Answer: {sample['label']}")
+print(f"Images: {sample['images']}")
+```
+
+## Citation
+
+If you use this benchmark, please cite our work:
+
+```bibtex
+@misc{ji2025visualtransbenchmarkrealworldvisual,
+      title={VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning}, 
+      author={Yuheng Ji and Yipu Wang and Yuyang Liu and Xiaoshuai Hao and Yue Liu and Yuting Zhao and Huaihai Lyu and Xiaolong Zheng},
+      year={2025},
+      eprint={2508.04043},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2508.04043}, 
+}
+```
+
+## License
+
+This dataset is released under the MIT License.
+
+## Contact
+
+For questions or issues, please open an issue on our [GitHub repository](https://github.com/WangYipu2002/VisualTrans) or contact the authors.