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qizekun/6DoF-SpatialBench

6-DoF SpatialBench Paper_link: https://arxiv.org/abs/2502.13143 Project Page: https://qizekun.github.io/sofar/ Github Code: https://github.com/qizekun/SoFar Previous spatial perception LLMs mainly focused on operations of positional relationships, such as left-right, near-far, size, and counting, etc. In actual object manipulation, the orientation of the object is also a very important factor. Therefore, we proposed a new 6-DoF spatial perception benchmark dataset for… See the full description on the dataset page: https://huggingface.co/datasets/qizekun/6DoF-SpatialBench.

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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6-DoF SpatialBench

Paper_link: https://arxiv.org/abs/2502.13143 <br> Project Page: https://qizekun.github.io/sofar/ <br> Github Code: https://github.com/qizekun/SoFar

Previous spatial perception LLMs mainly focused on operations of positional relationships, such as left-right, near-far, size, and counting, etc. In actual object manipulation, the orientation of the object is also a very important factor. Therefore, we proposed a new 6-DoF spatial perception benchmark dataset for evaluating the model's reasoning capabilities in position, orientation, and position-orientation relationships. We evaluated existing spatial perception models on this benchmark dataset.

The evaluation baseline is SoFar, a 6-DoF system for spatial reasoning and robotic manipulation.

Download the images.zip and extract it to ./datasets/6dof_spatialbench/. The overall directory structure should be:

│SoFar/datasets/6dof_spatialbench/
├── spatial_data.json
└── images/
    ├── 0.png
    └── ...
Data file nameSize
images.zip531.7 MB
spatial_data.json0.8 KB