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    • Synthetic dataset based on physical properties and forgery detection method for shadow-consistency analysis

    • Relevant experts have made new progress in the field of image and video synthesis detection, proposing a detection method that integrates physics and deep learning, innovatively combining illumination and shadow consistency analysis, effectively improving detection accuracy and adaptability, and providing new ideas for synthetic content detection.
    • Vol. 31, Issue 1, Pages: 99-119(2026)   

      Received:21 November 2024

      Revised:2025-04-03

      Accepted:09 April 2025

      Published:16 January 2026

    • DOI: 10.11834/jig.240705     

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  • Xue Ziyu, Liu Qingtong, Zhou Kangneng, Wang Wei, Jiang Xiuhua. 2026. Synthetic dataset based on physical properties and forgery detection method for shadow-consistency analysis. Journal of Image and Graphics, 31(1):0099-0119 DOI: 10.11834/jig.240705.
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相关作者

Liu Qingtong 国家广播电视总局广播电视科学研究院
Xue Ziyu 国家广播电视总局广播电视科学研究院
Cheng Xiao 国网重庆市电力公司电力科学研究院
Chen Tao 国网重庆市电力公司电力科学研究院
Zhou Lifang 重庆邮电大学计算机科学与技术学院;重庆邮电大学图像认知重庆市重点实验室
Zeng Hongquan 重庆邮电大学计算机科学与技术学院;重庆邮电大学图像认知重庆市重点实验室
Mi Jianxun 重庆邮电大学计算机科学与技术学院;重庆邮电大学图像认知重庆市重点实验室
Zhang Xinpeng 复旦大学计算与智能创新学院

相关机构

Academy of Broadcasting Science, NRTA
State Grid Chongqing Electric Power Company Electric Power Research Institute
Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications
School of Computer Science and Technology, Chongqing University of Posts and Telecommunications
College of Computer Science and Artificial Intelligence, Fudan University
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