activity
20142023
most citedCNN Based Adversarial Embedding with Minimum Alteration for Image Steganography

290 citations · 1k across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2023

Evading Detection Actively: Toward Anti-Forensics against Forgery Localization

Long Zhuo, Shenghai Luo, Shunquan Tan +3

Anti-forensics seeks to eliminate or conceal traces of tampering artifacts. Typically, anti-forensic methods are designed to deceive binary detectors and persuade them to misjudge…

cs.CV2022

STD-NET: Search of Image Steganalytic Deep-learning Architecture via Hierarchical Tensor Decomposition

Shunquan Tan, Qiushi Li, Laiyuan Li +2

Recent studies shows that the majority of existing deep steganalysis models have a large amount of redundancy, which leads to a huge waste of storage and computing resources. The e…

cs.CV2021★ 110 cited

Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localization

Long Zhuo, Shunquan Tan, Bin Li +1

Image editing techniques enable people to modify the content of an image without leaving visual traces and thus may cause serious security risks. Hence the detection and localizati…

cs.MM2021★ 42 cited

MCTSteg: A Monte Carlo Tree Search-based Reinforcement Learning Framework for Universal Non-additive Steganography

Xianbo Mo, Shunquan Tan, Bin Li +1

Recent research has shown that non-additive image steganographic frameworks effectively improve security performance through adjusting distortion distribution. However, as far as w…

cs.CV2021

Image Steganography based on Iteratively Adversarial Samples of A Synchronized-directions Sub-image

Xinghong Qin, Shunquan Tan, Bin Li +2

Nowadays a steganography has to face challenges of both feature based staganalysis and convolutional neural network (CNN) based steganalysis. In this paper, we present a novel steg…

cs.CV2020

Boosting CNN-based primary quantization matrix estimation of double JPEG images via a classification-like architecture

Benedetta Tondi, Andrea Costranzo, Dequ Huang +1

Estimating the primary quantization matrix of double JPEG compressed images is a problem of relevant importance in image forensics since it allows to infer important information ab…