详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Wei Song, Yuxin Cao, Zhenchang Xing, Liming Zhu, Jin Song Dong, Yulei Sui, Jingling Xue
- 文章类型
- PAPER
- 语言
- en
- 发布日期
- 2026-08-05
摘要
arXiv:2608.03165v1 Announce Type: cross Abstract: Invisible image watermarks are increasingly used for deepfake detection and provenance tracking, where they must survive not only incidental distortions but also deliberate removal. We revisit spread-spectrum embedding, a classical watermarking principle, inside a modern neural post-hoc watermarking architecture. Our starting point is a measurement: in existing encoder-decoder schemes each message bit occupies only a small fraction of the image, a shared contributing factor to their fragility, since removal then need only disturb the region a bit occupies. SpreadMark instead spreads each bit as a dense pseudo-random codeword over the whole image and recovers it by matched-filtering a learned cover-suppressed chip representation, with a parallel convolutional decoding path and sparsification-aware training.
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