6 datasets found

Video question answering (VideoQA) is an essential task in vision-language understanding, which has attracted numerous research attention recently. Nevertheless, existing works...

Video question answering (VideoQA) requires systems to understand the visual information and infer an answer for a natural language question from it.

InternVid: A large-scale video-text dataset for multimodal understanding and generation.

The TGIF-QA dataset consists of 165165 QA pairs chosen from 71741 animated GIFs. To evaluate the spatiotemporal reasoning ability at the video level, TGIF-QA dataset designs...

The dataset used in the paper is MSR-VTT, a large video description dataset for bridging video and language. The dataset contains 10k video clips with length varying from 10 to...

Youtube-8M is a large-scale video classification benchmark.