通过维度感知映射统一水印技术
Unifying Watermarking via Dimension-Aware Mapping
AI总结：
DiM通过维度感知映射统一水印技术，在视频领域实现不同维度嵌入与提取以提升水印能力。
摘要：
深度水印方法通常具有相似的编码器-解码器架构，但在功能行为上存在显著差异。我们提出DiM，一种新的多维水印框架，将水印技术建模为维度感知映射问题，从而在功能层面统一现有水印方法。在DiM中，水印信息被建模为不同维度的负载，包括一维二进制消息、二维空间掩码和三维时空结构。我们发现嵌入和提取的维度配置很大程度上决定了最终的水印行为。同维度映射保持负载结构并支持细粒度控制，而跨维度映射能够实现空间或时空定位。我们将在视频领域实例化DiM，其中时空表示能够实现更广泛的维度映射。实验表明，仅通过改变嵌入和提取的维度，而不改变架构，可以导致不同的水印能力，包括时空篡改定位、局部嵌入控制以及在帧中断下的时间顺序恢复。
英文摘要：
Deep watermarking methods often share similar encoder-decoder architectures, yet differ substantially in their functional behaviors. We propose DiM, a new multi-dimensional watermarking framework that formulates watermarking as a dimension-aware mapping problem, thereby unifying existing watermarking methods at the functional level. Under DiM, watermark information is modeled as payloads of different dimensionalities, including one-dimensional binary messages, two-dimensional spatial masks, and three-dimensional spatiotemporal structures. We find that the dimensional configuration of embedding and extraction largely determines the resulting watermarking behavior. Same-dimensional mappings preserve payload structure and support fine-grained control, while cross-dimensional mappings enable spatial or spatiotemporal localization. We instantiate DiM in the video domain, where spatiotemporal representations enable a broader set of dimension mappings. Experiments demonstrate that varying only the embedding and extraction dimensions, without architectural changes, leads to different watermarking capabilities, including spatiotemporal tamper localization, local embedding control, and recovery of temporal order under frame disruptions.
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