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| | license: apache-2.0 |
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| | |
| | # OSCBench Dataset |
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| | ### Dataset Description |
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| | OSCBench is a benchmark dataset designed to evaluate **object state change (OSC)** reasoning in text-to-video (T2V) generation models. |
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| | OSCBench organizes prompts into three scenario types: |
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| | - **Regular scenarios:** common action–object combinations frequently seen in training data. |
| | - **Novel scenarios:** uncommon but physically plausible action–object pairs that test generalization. |
| | - **Compositional scenarios:** prompts that combine multiple actions or conditions to test compositional reasoning. |
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| | ### Dataset Statistics |
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| | The OSCBench dataset contains **1,120 prompts** organized into three scenario categories: |
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| | | Scenario Type | Number of Scenarios | Prompts per Scenario | Total Prompts | |
| | |---------------|---------------------|----------------------|--------------| |
| | | Regular | 108 | 8 | 864 | |
| | | Novel | 20 | 8 | 160 | |
| | | Compositional | 12 | 8 | 96 | |
| | | **Total** | **140** | — | **1,120** | |
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| | ### Dataset Sources |
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| | - **Dataset:** https://huggingface.co/datasets/XianjingHan/OSCBench_Dataset |
| | - **Paper:** https://arxiv.org/abs/2603.11698 |
| | - **Project Page:** https://hanxjing.github.io/OSCBench |
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| | |
| | ## Acknowledgements and Citation |
| | |
| | If you find this dataset helpful, please consider citing the original work: |
| | |
| | ```bash |
| | @article{han2026oscbench, |
| | title={OSCBench: Benchmarking Object State Change in Text-to-Video Generation}, |
| | author={Han, Xianjing and Zhu, Bin and Hu, Shiqi and Li, Franklin Mingzhe and Carrington, Patrick and Zimmermann, Roger and Chen, Jingjing}, |
| | journal={arXiv preprint arXiv:2603.11698}, |
| | year={2026} |
| | } |
| | ``` |
