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Sun Yat-sen University
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NullEdit achieves a remarkable 0.813 reduction in EditReward IF scores, effectively neutralizing harmful image edits without compromising the visual quality or identity of the original image.
Achieve state-of-the-art image manipulation localization by unifying low-level frequency cues and high-level semantic priors, enabling robust detection of both traditional and diffusion-generated edits.
