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#3313
in ICLR 2025
of 3827 papers
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Abstract
Recent advances in image-to-image editing models offer both benefits and risks. While they enhance creativity, accessibility, and applications in fields ranging from medicine to environmental science, they can also enable misuse, such as identity manipulation, copyright infringement, and deepfake creation. This blog explores methods to protect images from such misuse, reproduces findings from relevant research, and extends them across various models and datasets.
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