English

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

Artificial Intelligence 2024-09-18 v2

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}

Keywords

Cite

@article{arxiv.2408.11347,
  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},
  journal= {arXiv preprint arXiv:2408.11347},
  year   = {2024}
}

Comments

5 pages, 1 figure, 1 table, accepted in Embodied AI 2024 Workshop held in conjunction with CVPR 2024