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+ # SPARK (multi-vision Sensor Perception And Reasoning benchmarK)
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+ <!-- Provide a quick summary of the dataset. -->
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+ SPARK that can reduce the fundamental multi-vision sensor information gap between images and multi-vision sensors. We generated 6,248 vision-language test samples automatically to investigate multi-vision sensory perception and multi-vision sensory reasoning on physical sensor knowledge proficiency across different formats, covering different types of sensor-related questions.
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+ ## Dataset Details
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+ ## Uses
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+ <!-- Address questions around how the dataset is intended to be used. -->
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+ ### Direct Use
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+ <!-- This section describes suitable use cases for the dataset. -->
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+ ### Source Data
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+ #### Data Collection and Processing
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+ These instructions are built from five public datasets: MS-COCO, M3FD, Dog&People, RGB-D scene dataset, and UNIFESP X-ray Body Part Classifier Competition dataset.
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+ ## Citation
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+ <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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+ **BibTeX:**
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+ [More Information Needed]
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+ **APA:**
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+ [More Information Needed]
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+ ## Contact
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+ [SangYun Chung](https://sites.google.com/view/sang-yun-chung/profile): [email protected]