Projects

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    Proactive Image Manipulation Detection

    Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu

    Image manipulation detection algorithms are often trained to discriminate between images manipulated with particular Generative Models (GMs) and genuine/real images, yet generalize poorly to images manipulated with GMs unseen in the training. Conventional detection algorithms receive an input image passively. By contrast, we propose a proactive scheme to image ...

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    Keywords: Deepfake, Image Forgery

Publications

2022

  • Proactive Image Manipulation Detection
    Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, Jun. 2022
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
  • @inproceedings{ proactive-image-manipulation-detection,
      author = { Vishal Asnani and Xi Yin and Tal Hassner and Sijia Liu and Xiaoming Liu },
      title = { Proactive Image Manipulation Detection },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { New Orleans, LA },
      month = { June },
      year = { 2022 },
    }
  • Reverse Engineering of Imperceptible Adversarial Image Perturbations
    Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
    In Proceeding of The International Conference on Learning Representations (ICLR 2022), Virtual, Apr. 2022
    Bibtex | PDF
  • @inproceedings{ reverse-engineering-of-imperceptible-adversarial-image-perturbations,
      author = { Yifan Gong and Yuguang Yao and Yize Li and Yimeng Zhang and Xiaoming Liu and Xue Lin and Sijia Liu },
      title = { Reverse Engineering of Imperceptible Adversarial Image Perturbations },
      booktitle = { In Proceeding of The International Conference on Learning Representations },
      address = { Virtual },
      month = { April },
      year = { 2022 },
    }