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

Source: [The Solution for the ICCV 2023 Perception Test Challenge 2023 -- Task 6 -- Grounded videoQA](<https://www.sota2.com/research/paper/68fa73e61e209131cea5ec0c>)

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

Data updated: 2025-10-26T02:58:03.881Z

Authors: Hailiang Zhang, Dian Chao, Zhihao Guan, Yang Yang

Published: 2024-07-02T03:13:27.000Z

## 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.

## 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/2407.01907>)

[PDF](<https://arxiv.org/pdf/2407.01907.pdf>)