A zero-shot steganalysis framework integrates hiding, revealing, and detection with residual augmentation to recover secrets and generalize across datasets and architectures for invertible image hiding.
Depth-wise separable convolutions and multi-level pooling for an efficient spatial CNN-based steganalysis,
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Zero-Shot Interpretable Image Steganalysis for Invertible Image Hiding
A zero-shot steganalysis framework integrates hiding, revealing, and detection with residual augmentation to recover secrets and generalize across datasets and architectures for invertible image hiding.