An Anti-Steganalysis HEVC Video Steganography With High Performance Based on CNN and PU Partition Modes-Reference-Cited by-同舟云学术

An Anti-Steganalysis HEVC Video Steganography With High Performance Based on CNN and PU Partition Modes

Published:2023-01-01 Issue:1 Volume:20 Page:606-619
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Li Zhonghao¹^ORCID,Jiang Xinghao¹^ORCID,Dong Yi¹^ORCID,Meng Laijin¹^ORCID,Sun Tanfeng¹^ORCID

Affiliation:

1. National Engineering Lab on Information Content Analysis Techniques, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8858/10016903/09672694.pdf?arnumber=9672694

Reference41 articles.

1. Video steganography with perturbed macroblock partition

2. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

3. Comparison of the Coding Efficiency of Video Coding Standards—Including High Efficiency Video Coding (HEVC)

4. HEVC reference model HM 16.15 GitLab,2014

5. Dense Residual Convolutional Neural Network based In-Loop Filter for HEVC

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generative Steganography via Live Comments on Streaming Video Frames;IEEE Transactions on Computational Social Systems;2024-06

2. Blast furnace raw material granularity recognition model based on deep learning and multimodal fusion of 3D point cloud;The Visual Computer;2024-05-25

3. Global texture sensitive convolutional transformer for medical image steganalysis;Multimedia Systems;2024-05-23

4. Adaptive HEVC video steganograhpy based on PU partition modes;Journal of Visual Communication and Image Representation;2024-05

5. Quality Enhancement with Frame-wise DLCNN using High Efficiency Video Coding in 5G Networks;Scalable Computing: Practice and Experience;2024-02-24