NExT-QA is a VideoQA benchmark targeting the explanation of video contents. It challenges QA models to reason about the causal and temporal actions and understand the rich object interactions in daily activities, e.g., "why is the boy crying?" and "How does the lady react after the boy fall backward?". It supports both multi-choice and generative open-ended QA tasks. The videos are untrimmed and the questions usually invoke local video contents for answers.
Variants: NExT-QA, NExT-GQA, NExT-QA (Open-ended VideoQA)
This dataset is used in 1 benchmark:
Recent papers with results on this dataset: