Multi-modality (MM) image fusion aims to render fused images that maintain the merits of
different modalities, eg, functional highlight and detailed textures. To tackle the challenge in …

Data hiding is the art of concealing messages with limited perceptual changes. Recently,
deep learning has enriched it from various perspectives with significant progress. In this …

In the era of AI-generated content (AIGC) malicious tampering poses imminent threats to
copyright integrity and information security. Current deep image watermarking while widely …

Image steganography aims to hide secret images into a container image, where the secret is
hidden from human vision and can be restored when necessary. Previous image …

Abstract Neural Radiance Fields (NeRF) have the potential to be a major representation of
media. Since training a NeRF has never been an easy task, the protection of its model …

Recently, generative steganography that transforms secret information to a generated image
has been a promising technique to resist steganalysis detection. However, due to the …

Current image steganography techniques are mainly focused on cover-based methods,
which commonly have the risk of leaking secret images and poor robustness against …

Video steganography is the art of unobtrusively concealing secret data in a cover video and
then recovering the secret data through a decoding protocol at the receiver end. Although …

As a promising technique of resisting steganalysis detection, generative steganography
usually generates a new image driven by secret information as the stego-image. However, it …

Recent advancements in neural rendering have paved the way for a future marked by the
widespread distribution of visual data through the sharing of Neural Radiance Field (NeRF) …