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李文杰(女)




姓    名李文杰

职    称讲师

导师类型

电子邮箱wenjieli@email.tjut.edu.cn

办公地点:1-305

研究方向:多媒体内容取证、AI安全、信息隐藏等


(1)国家自然科学基金,青年项目,在研,主持

(2)国家自然科学基金,面上项目,在研,参与

(3)北京市自然科学基金,面上项目,在研,参与


代表性论文

[1] Li Wenjie, Li Xiaolong, Ni Rongrong, and Zhao Yao. Quantization step estimation for JPEG image forensics[J]. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022, 32(7): 4816-4827. (SCI一区Top)

[2] Li Wenjie, Li Xiaolong, Ni Rongrong, and Zhao Yao. PVO-based reversible data hiding using adaptive multiple histogram generation and modification[J]. Signal Processing: Image Communication (SPIC), 2021, 99: 116405. (SCI二区)

[3] Li Wenjie, Ni Rongrong, Li Xiaolong, and Zhao Yao. Robust median filtering detection based on the difference of frequency residuals[J]. Multimedia Tools and Applications (MTAP), 2019, 78 (7): 8363-8381.

[4] Li Wenjie, Tondi Benedetta, Ni Rongrong, and Barni Mauro. Increased-confidence adversarial examples for deep learning counter-forensics[C]//International Conference on Pattern Recognition (ICPR), 2021: 411-424.

[5] Li Wenjie, Ni Rongrong, and Zhao Yao. JPEG photo privacy-preserving algorithm based on sparse representation and data hiding[C]//International Conference on Image and Graphics (ICIG), 2017: 575-586. (最佳论⽂奖)

[6] Yu Yang, Ni Rongrong, Li Wenjie, and Zhao Yao. Detection of AI-manipulated fake faces via mining generalized features[J]. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). 2022, 18(4): 1-23.

[7] Barni Mauro, Li Wenjie, Tondi Benedetta, and Zhang Bowen. Adversarial examples in image forensics[M]//Multimedia Forensics. Springer, 2022.

[8] Yang Dongdong, Li Wenjie, Ni Rongrong, and Zhao Yao. Enhancing adversarial examples transferability via ensemble feature manifolds[C]//Proceedings of International Workshop on Adversarial Learning for Multimedia, 2021: 49-54.

[9] Wang Xiying, Ni Rongrong, Li Wenjie, and Zhao Yao. Adversarial attack on fake-faces detectors under white and black box scenarios[C]//International Conference on Image Processing (ICIP), 2021: 3627-3631.


(1)国际会议ICIG,2017最佳论文奖



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