3 papers
cs.CV2025
TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning
Fengchun Liu. Tong Zhang, Chunying Zhang
For deep learning-based image steganography frameworks, in order to ensure the invisibility and recoverability of the information embedding, the loss function usually contains seve…
cs.CV2025
STCL:Curriculum learning Strategies for deep learning image steganography models
Fengchun Liu, Tong Zhang, Chunying Zhang
Aiming at the problems of poor quality of steganographic images and slow network convergence of image steganography models based on deep learning, this paper proposes a Steganograp…
cs.CV2025
CLPSTNet: A Progressive Multi-Scale Convolutional Steganography Model Integrating Curriculum Learning
Fengchun Liu, Tong Zhang, Chunying Zhang
In recent years, a large number of works have introduced Convolutional Neural Networks (CNNs) into image steganography, which transform traditional steganography methods such as ha…