VLM-Video-Action-Localization

This repository provides a sample code of a paper, Open-vocabulary action localization with iterative visual prompting (IEEE Access). This paper was authored by the Applied Robotics Research team.

Overview of the pipeline:

How to use

We have confirmed that the sample codes work with python 3.12.1

Modify the auth.env

If you use Azure OpenAI

• AZURE_OPENAI_DEPLOYMENT_NAME
• AZURE_OPENAI_ENDPOINT
• AZURE_OPENAI_API_KEY

  If you use OpenAI

• OPENAI_API_KEY

Install dependencies

> pip install -r requirements.txt

Run the sample code

python example.py --credentials auth.env --video sample_video/sample.mp4 --grid 3 --action "Grasping the can"

The --grid N option specifies the number of frames to extract, creating an image with an NxN grid tiling.

Bibliography

@article{wake2025open,
  author={Wake, Naoki and Kanehira, Atsushi and Sasabuchi, Kazuhiro and Takamatsu, Jun and Ikeuchi, Katsushi},
  journal={IEEE Access}, 
  title={Open-Vocabulary Action Localization With Iterative Visual Prompting}, 
  year={2025},
  volume={13},
  number={},
  pages={56908--56917},
  doi={10.1109/ACCESS.2025.3555167}}

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