3 papers
cs.CR2026
Plug-and-Hide: Provable and Adjustable Diffusion Generative Steganography
Jiahao Zhu, Zixuan Chen, Jiali Liu +3
Diffusion model-based generative image steganography (DM-GIS) is an emerging paradigm that leverages the generative power of diffusion models to conceal secret messages without req…
cs.MM2026
Rethinking Security of Diffusion-based Generative Steganography
Jihao Zhu, Zixuan Chen, Jiali Liu +4
Generative image steganography is a technique that conceals secret messages within generated images, without relying on pre-existing cover images. Recently, a number of diffusion m…
cs.CV2025
Training-Free Class Purification for Open-Vocabulary Semantic Segmentation
Qi Chen, Lingxiao Yang, Yun Chen +4
Fine-tuning pre-trained vision-language models has emerged as a powerful approach for enhancing open-vocabulary semantic segmentation (OVSS). However, the substantial computational…