Xuanhang Chang

MaxMark: High-Capacity Diffusion-Native Watermarking via Robust and Invertible Latent Embedding

Diffusion-native watermarking provides a more secure and reliable way to trace images from latent diffusion models (LDMs) by embedding information directly into the generative process. However, existing methods suffer from a fundamental limitation: their embedding capacity is extremely small. We int