The Solution for the ICCV 2023 Perception Test Challenge 2023 -- Task 6 -- Grounded videoQA

TL;DR

This paper presents a grounded video question-answering method for the ICCV 2023 challenge, combining VALOR and TubeDETR models to improve object tracking and visual grounding in videos.

Contribution

It introduces a two-stage approach that integrates VALOR for answering questions and TubeDETR for generating bounding boxes, addressing limitations of previous methods.

Findings

Enhanced accuracy in visual grounding and object tracking.

Effective handling of questions involving object movement over time.

Improved performance on the ICCV 2023 perception test challenge.

Abstract

In this paper, we introduce a grounded video question-answering solution. Our research reveals that the fixed official baseline method for video question answering involves two main steps: visual grounding and object tracking. However, a significant challenge emerges during the initial step, where selected frames may lack clearly identifiable target objects. Furthermore, single images cannot address questions like "Track the container from which the person pours the first time." To tackle this issue, we propose an alternative two-stage approach:(1) First, we leverage the VALOR model to answer questions based on video information.(2) concatenate the answered questions with their respective answers. Finally, we employ TubeDETR to generate bounding boxes for the targets.