# Video based Contextual Question Answering

Source: [Video based Contextual Question Answering](<https://www.sota2.com/research/paper/68fa64401e209131cea03798>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T05:54:50.233Z

Authors: Akash Ganesan, Divyansh Pal, Karthik Muthuraman, Shubham Dash

Published: 2018-04-19T23:06:00.000Z

## Abstract

The primary aim of this project is to build a contextual Question-Answering model for videos. The current methodologies provide a robust model for image based Question-Answering, but we are aim to generalize this approach to be videos. We propose a graphical representation of video which is able to handle several types of queries across the whole video. For example, if a frame has an image of a man and a cat sitting, it should be able to handle queries like, where is the cat sitting with respect to the man? or ,what is the man holding in his hand?. It should be able to answer queries relating to temporal relationships also.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1804.07399>)

[PDF](<https://arxiv.org/pdf/1804.07399.pdf>)