智能系统学报2025，Vol.20Issue(2)：283-304,22.DOI:10.11992/tis.202403004
基于深度学习的图像篡改检测方法综述
A review of image tampering detection methods based on deep learning
摘要
Abstract
With the increasing popularity of digital image editing tools,image tampering has become much easier.A large number of tampered false images are now circulating on the Internet and social media,threatening the authenticity and credibility of critical domains such as law,journalism,and scientific research.Image tampering detection aims to identify and locate altered areas within tampered images,thereby safeguarding their credibility.This paper provides a comprehensive review of deep learning-based methods for image tampering detection.First,it introduces the current re-search status in this field.Next,it classifies deep learning approaches developed over the past five years.The paper also highlights the main datasets and evaluation metrics used,along with a performance comparison of various methods.Fi-nally,it discusses the limitations of current tampering detection methods and offers insights into future development dir-ections.关键词
深度学习/图像篡改检测/计算机视觉/卷积神经网络/图像处理/图像取证/图像伪造/伪造检测Key words
deep learning/image tempering detection/computer vision/convolutional neural network/image pro-cessing/image forensic/image forgery/forgery detection分类
信息技术与安全科学引用本文复制引用
张汝波,蔺庆龙,张天一..基于深度学习的图像篡改检测方法综述[J].智能系统学报,2025,20(2):283-304,22.基金项目
国家自然科学基金项目(62202024) （62202024）
中央高校基本科研业务费专项资金项目(501QYJC2024139006). （501QYJC2024139006）
