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  It focuses on measuring how well a world model can generate driving scenes conditioned on specified trajectories.
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- <img src="https://github.com/turingmotors/ACT-Bench/blob/main/assets/overview.png" alt="Overview of the Dataset" width="600">
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- For more details, please refer our [paper]() and [repository](https://github.com/turingmotors/ACT-Bench).
 
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  ## Data fields
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  If you find our work helpful, please feel free to cite us.
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  ```bibtex
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- @misc{arai2024actbenchactioncontrollableworld,
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  title={ACT-Bench: Towards Action Controllable World Models for Autonomous Driving},
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  author={Hidehisa Arai and Keishi Ishihara and Tsubasa Takahashi and Yu Yamaguchi},
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  year={2024},
 
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  It focuses on measuring how well a world model can generate driving scenes conditioned on specified trajectories.
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+ <img src="fig1.png" alt="Overview of the ACT-Bench" width="800">
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+ For more details, please refer our [paper](https://arxiv.org/abs/2412.05337) and [code repository](https://github.com/turingmotors/ACT-Bench).
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  ## Data fields
 
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  If you find our work helpful, please feel free to cite us.
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  ```bibtex
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+ @misc{arai2024actbench,
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  title={ACT-Bench: Towards Action Controllable World Models for Autonomous Driving},
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  author={Hidehisa Arai and Keishi Ishihara and Tsubasa Takahashi and Yu Yamaguchi},
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  year={2024},