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SHIELDLogo: An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models

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Overview

In this paper, we conduct a detailed comparison of two models: Google's Gemini Gemini and OpenAI's GPT-4V(ision) GPT-4V. We utilize Zero-Shot/One-Shot as well as COT methods to comprehensively analyze the performance of these two models in FAS and Face Forgery Detection tasks.Meanwhile, we introduce a novel MCOT method, which has been empirically validated to significantly enhance detection accuracy.

Release

  • [2024/2/7]🔥🔥🔥We released the evaluation result Arxiv Paper (about 100 pages) and the code.

🔗 Citation

If you find our work helpful, please cite:

@article{shi2024shield,
  title={SHIELD: An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models},
  author={Shi, Yichen and Gao, Yuhao and Lai, Yingxin and Wang, Hongyang and Feng, Jun and He, Lei and Wan, Jun and Chen, Changsheng and Yu, Zitong and Cao, Xiaochun},
  journal={arXiv preprint arXiv:2402.04178},
  year={2024}
}

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