Randomly masking 60 to 80 percent of input patches while fine-tuning a pre-trained CLIP-ResNet50 produces a detector that reaches 92.7% average accuracy on GenImage with 1% training data, outperforming the prior state of the art by 13.6%.
New find- ing and unified framework for fake image detection
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Learning on Less: Constraining Pre-trained Model Learning for Generalizable Diffusion-Generated Image Detection
Randomly masking 60 to 80 percent of input patches while fine-tuning a pre-trained CLIP-ResNet50 produces a detector that reaches 92.7% average accuracy on GenImage with 1% training data, outperforming the prior state of the art by 13.6%.