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[TCSVT 2024] The released code of paper "Video Question Generation for Dynamic Changes"

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D-VQG

This repository contains the PyTorch implementation of paper "Video Question Generation for Dynamic Changes" on IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) 2024.

Overview

A video contains dynamically changing visual content that deserves to be questioned, e.g., changes in object motions, object states and relationships among objects, which is more practical and closer to the dynamic world we live in. In this paper, we propose a difference-aware video question generation model that aims to generate questions about temporal differences in the video.

image-20240324222520195

Installation

  • Install Anaconda or Miniconda distribution based on Python3.10
  • Main packages: PyTorch = 1.10, transformers = 4.30

Training & Evaluation

python train.py

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[TCSVT 2024] The released code of paper "Video Question Generation for Dynamic Changes"

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