EgoTaskQA

该数据集名为EgoTaskQA，它为理解人类任务提供了一个基准，通过在真实世界的第一人称视角视频上进行问答，旨在探究动作的依赖性、意图以及行动者的信念。问题被分为描述性、预测性、解释性和反事实性类型，以分析对空间、时间和因果关系的理解。该数据集的任务是视频问答。

This dataset, named EgoTaskQA, serves as a benchmark for human task understanding. By conducting question-answering tasks on real-world first-person perspective videos, it aims to investigate action dependencies, intentions, and agents' beliefs. The questions are categorized into four types: descriptive, predictive, explanatory, and counterfactual, to analyze the comprehension of spatial, temporal, and causal relationships. The core task of this dataset is video question answering.