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arXiv · 2112.09581

Watermarking Images in Self-Supervised Latent Spaces

Pierre Fernandez·Alexandre Sablayrolles·Teddy Furon·Hervé Jégou·Matthijs Douze
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Abstract

We revisit watermarking techniques based on pre-trained deep networks, in the light of self-supervised approaches. We present a way to embed both marks and binary messages into their latent spaces, leveraging data augmentation at marking time. Our method can operate at any resolution and creates watermarks robust to a broad range of transformations (rotations, crops, JPEG, contrast, etc). It significantly outperforms the previous zero-bit methods, and its performance on multi-bit watermarking is on par with state-of-the-art encoder-decoder architectures trained end-to-end for watermarking. The code is available at github.com/facebookresearch/ssl_watermarking

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Pierre Fernandez, Alexandre Sablayrolles, Teddy Furon, Hervé Jégou, Matthijs Douze. 2021-12-17. Watermarking Images in Self-Supervised Latent Spaces. https://arxiv.org/abs/2112.09581

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