Video/image forensics, Game theory, adversarial machine learning
https://scholar.google.ca/citations?user=__LlM6MAAAAJ H-index: 13
zengh5atmail2.sysu.edu.cn, we have a few PG positions (either international or local) until the end of May, 2026.
Hui Zeng, and X. Kang, “Fast source camera identification using content adaptive guided image filter,” Journal of forensic sciences, 61(2): 520–526, 2016 pdf
Hui Zeng, and A. Peng, and X. Lin, and S. Luo, “Source smartphone identification for digital zoomed images,” Proceedings of the ACM Turing Celebration Conference-China, pp. 1–6, 2019, ACM. paper
Hui Zeng, and Y. Wan, and K. Deng, and A. Peng, “Source Camera Identification with Dual-Tree Complex Wavelet Transform,” IEEE Access, 8: 18874–18883 pdf code-Matlab code-Python
Hui Zeng, and Y. Zhan, and X. Kang, and X. Lin, “Image splicing localization using PCA-based noise level estimation,” Multimedia Tools and Applications, 76(4): 4783–4799, 2017 pdf
Hui Zeng, A. Peng, and X. Lin, “Exposing Image splicing with inconsistent sensor noise levels,” Multimedia Tools and Applications, 2020, 79: 26139–26154. pdf
Hui Zeng, K. Deng, A. Peng, “ISO Setting Estimation Based on Convolutional Neural Network and Its Application in Image Forensics,” IWDW2020, Melbourne (online) 2020.11.25–27 paper
M. D. M. Hosseini, Miroslav Goljan, and Hui Zeng, "Semi-Blind Image Resampling Factor Estimation for PRNU Computation," in Proc. IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics, 2020, pp 77-1 - 77-11 pdf
Hui Zeng, M. D. M. Hosseini, and M. Goljan, 'Replacing DWT with DTCWT in blind image rotation angle estimation,' in Proc. IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics, 2021. pdf
Kun Yu, R. Yang, Hui Zeng, and A. Peng, "Joint estimation of image rotation angle and scaling factor," APSIPA2021, pp. 1716–1721. paper
Kun Yu, M. D. M. Hosseini, A. Peng, Hui Zeng, M. Goljan, "Make your enemy your friend: improving image rotation angle estimation with harmonics," 2023ICASSP. doi: 10.1109/ICASSP49357.2023.10095317 pdf code
Tong Zhang, A. Peng, Hui Zeng, 'Ignored Details in Eyes: Exposing GAN-generated Faces by Sclera,' 2023ICONIP, pp 563–574, Changsha, session chair. Paper Code
New Weinan Zhang, S. Cui, Q. Zhang, B. Chen, Hui Zeng, Q. Zhong, 'Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Images Detection,' Mathematics, 2025, 13(9), 1372.
Hui Zeng, and J. Chen, and X. Kang, and W. Zeng, “Removing camera fingerprint to disguise photograph source,” 2015 IEEE International Conference on Image Processing (ICIP), 1687–1691 pdf
J. Wu and Z. Wang, and Hui Zeng, and X. Kang, “Multiple-Operation Image Anti-Forensics with WGAN-GP Framework,” 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 1303–1307, pdf
Hui Zeng, A. Peng, and X. Kang, “Hiding traces of camera anonymization by Poisson blending,” International Conference on Artificial Intelligence and Security (ICAIS2020), pp. 98–108, paper
Hui Zeng, and X. Kang, and J. Huang, “Mixed-strategy Nash equilibrium in the camera source identification game,” 2013 IEEE International Conference on Image Processing, 4472–4476 pdf
Hui Zeng, and Y. Jiang, and X. Kang, and L. Liu, “Game theoretic analysis of camera source identification,” 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 1–9. pdf
Hui Zeng, and X. Kang, “Camera source identification game with incomplete information,” International Workshop on Digital Watermarking, 192–204, 2013, (Best student paper) pdf
Hui Zeng, and J. Liu, and J. Yu, and X. Kang, and Y. Shi, and Z Jane Wang “A framework of camera source identification Bayesian game,” IEEE transactions on cybernetics, 47(7): 1757–1768, 2016 pdf
Hui Zeng, and T. Qin, and X. Kang, and L. Liu, “Countering anti-forensics of median filtering,” 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2704-2708 pdf
Y. Jiang and Hui Zeng, and X. Kang, and Li Liu, “The game of countering JPEG anti-forensics based on the noise level estimation,” 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 1–9. pdf
Hui Zeng, and J. Yu, and X. Kang, and Siwei Lyu, “Countering JPEG anti-forensics based on noise level estimation,” Science China Information Sciences, 61(3): 032103, 2018, pdf
Hui Zeng, and X. Kang, and A. Peng, “A multi-purpose countermeasure against image anti-forensics using autoregressive model,” Neurocomputing, 189: 117–122, 2016 paper
Hui Zeng, “Rebuilding the credibility of sensor-based camera source identification,” Multimedia Tools and Applications, 75: 13871—13882, 2016. paper
A. Peng, K. Deng, J. Zhang, S. Luo，Hui Zeng，W. Yu, “Gradient-based adversarial image forensics,” the 27th International Conference on Neural Information Processing, pp. 417–428, 2020. paper
Kang Deng, A. Peng, Hui Zeng, "Detecting C&W adversarial images based on noise addition-then-denoising," ICIP2021, pp.3607–3611 pdf
Hui Zeng, K. Deng, B. Chen, A. Peng, "How secure are the adversarial examples themselves?" 2022ICASSP, pp. 2879–2883 pdf code
Zhi Lin, A. Peng, R. Wei, W. Yu, Hui Zeng, "An enhanced transferable adversarial attack of scale-invariant methods," 2022 IEEE International Conference on Image Processing (ICIP), pp. 3788-3792. pdf
A. Peng, C. Li, P. Zhu, X. Huang, Hui Zeng and W. Yu, "Countering the Anti-detection Adversarial Attacks", 2022ICONIP, paper
A. Peng, C. Li, P. Zhu, Z. Wu, K. Wang, Hui Zeng and W. Yu, "Effect of Image Down-sampling on Detection of Adversarial Examples", 2022ICONIP, paper
Zhi Lin, A. Peng, Hui Zeng, et al. "Boosting transferability of adversarial example via an enhanced EULER's method," 2023ICASSP, doi: 10.1109/ICASSP49357.2023.10096558 pdf
Hui Zeng, B. Chen, K. Deng, A. Peng, 'Adversarial example detection Bayesian game,' 2023 IEEE International Conference on Image Processing (ICIP), pp. 1710–1714. paper code
Hui Zeng, T. Zhang, B. Chen, A. Peng, 'Enhancing targeted transferability via suppressing high-confidence labels,' 2023ICIP, pp. 3309–3313. paper code
Zhi Lin, A. Peng, Hui Zeng, K. Wu, W. Yu, 'An enhanced neuron attribution-based attack via pixel dropping,' 2023ICIP, pp. 3439–3443. paper
Hui Zeng, B. Chen, R. Yang, et al. "Towards undetectable adversarial examples: a steganographic perspective," 2023ICONIP, pp. 172–183. paper code
Hui Zeng, B. Chen, A. Peng, 'Enhancing targeted transferability via feature space fine-tuning,' 2024ICASSP, pp. 4475–4479. paper code
A. Peng, G. Shi, Z. Lin, H. Zeng, X. Yang, "Approximating High-order Adversarial Attacks Using Runge-Kutta Methods," 2024, Tsinghua Science and Technology. paper
Qiang Wan, B. Chen, A. Peng, Hui Zeng, "A whale falls, all thrive: Mitigating attention gap to improve adversarial transferability," 2024ICPR, pp. 346–359. paper code
Hui Zeng, S. Cui, B. Chen, A. Peng, 'Everywhere Attack: Attacking Locally and Globally to Boost Targeted Transferability,' Proceedings of the AAAI Conference on Artificial Intelligence, 2025, 39(9), 9789–9796. code paper
Hui Zeng, S. Cui, B. Chen, A. Peng, 'Two Heads Are Better Than One: Averaging along Fine-Tuning to Improve Targeted Transferability,' IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India, 2025, pp. 1–5. code paper
Qiang Wan, S. Cui, A. Peng, Hui Zeng, R. Wei, 'Boosting Adversarial Transferability by Constructing Adversarial Trajectories,' 2025ICME.
New Qiang Wan, Hui Zeng, A. Peng, 'Enhancing Heterogeneous Model Transferability via Constrained Möbius Attack,' Pattern Recognition, 11329, 2026
New S Zhao, Z Liang, X Yang, H Gao, A Peng, H Zeng, 'ObjectAdv: Object-Level Unrestricted Adversarial Attacks via Diffusion Models' , 2026AAAI.
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