[R] Video Question Answering with Iterative Video-Text Co-Tokenization - Google 2022 - Reduces GFLOPs from 150-360 to only 67 while being able to achive new SOTAs in three main VideoQA benchmarks MSRVTT-QA, MSVD-QA and IVQA!

Paper: [https://arxiv.org/abs/2208.00934](https://arxiv.org/abs/2208.00934)

[https://ai.googleblog.com/2022/08/efficient-video-text-learning-with.html](https://ai.googleblog.com/2022/08/efficient-video-text-learning-with.html)

Abstract:

>Video question answering is a challenging task that requires understanding jointly the language input, the visual information in individual video frames, as well as the temporal information about the events occurring in the video. In this paper, we propose a novel **multi-stream video encoder for video question answering that uses multiple video inputs and a new video-text iterative co-tokenization approach to answer a variety of questions related to videos**. We experimentally evaluate the model on several …

benchmarks google iterative machinelearning qa question answering text tokenization video