CVJan 15, 2021

Recent Advances in Video Question Answering: A Review of Datasets and Methods

arXiv:2101.05954v221 citations
Originality Synthesis-oriented
AI Analysis

It provides a comprehensive overview for researchers in computer vision, but it is incremental as it reviews existing work without introducing new methods.

This survey reviews methods and datasets for Video Question Answering (VQA), a task that retrieves temporal and spatial information from videos, and it is the first such survey conducted for VQA.

Video Question Answering (VQA) is a recent emerging challenging task in the field of Computer Vision. Several visual information retrieval techniques like Video Captioning/Description and Video-guided Machine Translation have preceded the task of VQA. VQA helps to retrieve temporal and spatial information from the video scenes and interpret it. In this survey, we review a number of methods and datasets for the task of VQA. To the best of our knowledge, no previous survey has been conducted for the VQA task.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes