Multimodal Datasets and Benchmarks for Reasoning about Dynamic Spatio-Temporality in Everyday Environments
<|reference_start|>Multimodal Datasets and Benchmarks for Reasoning about Dynamic Spatio-Temporality in Everyday Environments: We used a 3D simulator to create artificial video data with standardized annotations, aiming to aid in the development of Embodied AI. Our question answering (QA) dataset measures the extent to which a robot can understand human behavior and the environment in a home setting. Preliminary experiments suggest our dataset is useful in measuring AI's comprehension of daily life. \end{abstract}<|reference_end|>
@article{ugai2024multimodal,
    title={Multimodal Datasets and Benchmarks for Reasoning about Dynamic
  Spatio-Temporality in Everyday Environments},
    author={Takanori Ugai, Kensho Hara, Shusaku Egami, Ken Fukuda},
    journal={arXiv preprint arXiv:2408.11347},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.11347},
    primaryClass={cs.AI}
}