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Code for the paper Red-Teaming Segment Anything Model accepted at CVPR 2024 4th Workshop of Adversarial Machine Learning on Computer Vision: Robustness of Foundation Models

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JankowskiChristopher/red-teaming-segment-anything-model

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Red-Teaming Segment Anything Model

Source code for the paper "Red-Teaming Segment Anything Model" accepted at CVPR 2024 4th Workshop of Adversarial Machine Learning on Computer Vision: Robustness of Foundation Models.

Repository contents

Repository contains 3 notebooks:

  • sam_style_transfer.ipynb - experiments to assess the quality of generated masks under different weather conditions.
  • sam_facial_recognition.ipynb - experiments to check whether LangSAM (version of Segment Anything with text prompts input) can unintentionally classify celebrities when prompted with a full name.
  • destroy_lang_sam.ipynb - experiments with adversarial attacks

Used code repositories

Our code uses parts of these repositories:

Ethical principals

Our research adheres to ethical principles and we expect all users to employ it responsibly and only for noble intentions.

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Code for the paper Red-Teaming Segment Anything Model accepted at CVPR 2024 4th Workshop of Adversarial Machine Learning on Computer Vision: Robustness of Foundation Models

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