Multimodal Datasets and Benchmarks for Reasoning about Dynamic Spatio-Temporality in Everyday Environments

Takanori Ugai, Kensho Hara, Shusaku Egami, Ken Fukuda
8/21/2024
cs.AI

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Abstract

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}

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Cite this paper

@article{ugai2024multimodal,
  title  = {Multimodal Datasets and Benchmarks for Reasoning about Dynamic Spatio-Temporality in Everyday Environments},
  author = {Takanori Ugai and Kensho Hara and Shusaku Egami and Ken Fukuda},
  year   = {2024},
  eprint = {2408.11347},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2408.11347v2}
}

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