Publications
A collection of my research work.
A Grey-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse
Zhongliang Guo, Chun Tong Lei, Lei Fang, Shuai Zhao, Yifei Qian, Jingyu Lin, Zeyu Wang, Cunjian Chen, Ognjen Arandjelović, Chun Pong Lau
IEEE Transactions on Information Forensics and Security (IEEE T-IFS), 2026
A VAE-targeted adversarial protection framework that leverages posterior collapse phenomena to prevent unauthorized image manipulation in latent diffusion models with minimal computational overhead.
Artwork Protection Against Unauthorized Neural Style Transfer and Aesthetic Color Distance Metric
Zhongliang Guo, Yifei Qian, Shuai Zhao, Junhao Dong, Yanli Li, Ognjen Arandjelović, Fang Lei, Chun Pong Lau
Pattern Recognition, 2026
A proactive protection method using adaptive adversarial perturbations to prevent unauthorized neural style transfer of artwork while preserving visual quality and resisting purification-based defenses.
Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack
Zhongliang Guo, Yifei Qian, Kaixuan Wang, Weiye Li, Ziheng Guo, Yuheng Wang, Yanli Li, Ognjen Arandjelović, Lei Fang
27th European Conference on Artificial Intelligence (ECAI Oral), 2024
A proactive protection method using frequency-adaptive perturbations to prevent unauthorized neural style transfer while preserving visual quality of original artwork.
A White-Box False Positive Adversarial Attack Method on Contrastive Loss-Based Offline Handwritten Signature Verification Models
Zhongliang Guo, Weiye Li, Yifei Qian, Ognjen Arandjelovic, Lei Fang
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
A novel white-box adversarial attack on signature verification models using style transfer with specialized loss functions to manipulate embedding distances while maintaining visual similarity.
A Siamese Transformer Network for Zero-Shot Ancient Coin Classification
Zhongliang Guo, Ognjen Arandjelović, David Reid, Yaxiong Lei, Jochen Büttner
Journal of Imaging, 2023
A pairwise matching approach for ancient coin identification using Siamese Vision Transformers, enabling robust attribution without requiring exemplars for every coin issue class.
A Method of Video Recognition Network of Face Tampering Based on Deep Learning
Zhongliang Guo, Dian Jia, Zhaokai Wang, Jiahang Wu, Yongqi Zhou
Patent, 2019
A convolutional neural network architecture with Inception modules for deepfake video detection, achieving 94.5% accuracy on FaceForensics++ through optimized hyperparameters and training strategies.
T2ICount: Enhancing Cross-modal Understanding for Zero-Shot Counting
Yifei Qian*, Zhongliang Guo*, Bowen Deng, Chun Tong Lei, Shuai Zhao, Chung Pong Lau, Xiaopeng Hong, Michael P Pound
Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR Highlight), 2025
A diffusion-based zero-shot object counting framework that enhances text sensitivity through hierarchical semantic correction and cross-attention supervision for fine-grained counting.
Threats and Defenses in the Federated Learning Life Cycle: A Comprehensive Survey and Challenges
Yanli Li, Zhongliang Guo, Nan Yang, Huaming Chen, Dong Yuan, Weiping Ding
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2025
A comprehensive survey of security threats and defense mechanisms throughout the federated learning lifecycle, analyzing utility-privacy trade-offs and identifying research gaps for trustworthy FL.
Instant Adversarial Purification with Adversarial Consistency Distillation
Chun Tong Lei, Hon Ming Yam, Zhongliang Guo, Yifei Qian, Chun Pong Lau
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
A single-step adversarial purification framework using distillation and controlled inference in diffusion models, achieving 100-fold speedup while maintaining robust defense against adversarial attacks.
A Survey of Recent Backdoor Attacks and Defenses in Large Language Models
Shuai Zhao, Meihuizi Jia, Zhongliang Guo, Leilei Gan, Xiaoyu Xu, Xiaobao Wu, Jie Fu, Feng Yichao, Fengjun Pan, Anh Tuan Luu
Transactions on Machine Learning Research (TMLR Survey Certification 🏆), 2025
A comprehensive survey of backdoor attacks on large language models, systematically categorizing attacks by fine-tuning methodology and identifying future research directions in LLM security.
DiffProtect: Generative Adversarial Examples Using Diffusion Models for Facial Privacy Protection
Jiang Liu, Chun Pong Lau, Zhongliang Guo, Yuxiang Guo, Zhaoyang Wang, Rama Chellappa
Pattern Recognition, 2025
A diffusion autoencoder-based method for generating semantically meaningful adversarial perturbations that protect facial images from unauthorized recognition systems with improved visual quality and attack success rates.
Semi-Supervised Crowd Counting with Masked Modeling: Facilitating Holistic Understanding of Crowd Scenes
Yifei Qian, Xiaopeng Hong, Zhongliang Guo, Ognjen Arandjelović, Carl R Donovan
IEEE Transactions on Circuits and Systems for Video Technology (IEEE T-CSVT), 2024
A semi-supervised crowd counting method that enhances model subitizing capability through masked prediction on unlabeled data, achieving robust performance with limited annotations.
Perspective-assisted Prototype-based Learning for Semi-supervised Crowd Counting
Yifei Qian, Liangfei Zhang, Zhongliang Guo, Xiaopeng Hong, Ognjen Arandjelović
Pattern Recognition, 2025
A prototype-based semi-supervised crowd counting method that captures perspective-aware density variations, enabling effective learning from limited labeled data through tailored consistency strategies.
Syntactic Paraphrase-based Synthetic Data Generation for Backdoor Attacks Against Chinese Language Models
Man Hu, Yatao Yang, Deng Pan, Zhongliang Guo, Luwei Xiao, Deyu Lin, Shuai Zhao
Information Fusion, 2025
A stealthy backdoor attack method for Chinese language models using LLM-generated syntactic paraphrasing as triggers, achieving high success rates while evading detection mechanisms.
Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity
Shuai Zhao, Yulin Zhang, Luwei Xiao, Xinyi Wu, Yanhao Jia, Zhongliang Guo, Xiaobao Wu, Cong-Duy Nguyen, Guoming Zhang, Anh Tuan Luu
IEEE Transactions on Affective Computing (IEEE T-AC), 2025
An automated evaluation framework investigating how emotional prompting affects large language models' performance and bias patterns in retinopathy of prematurity risk prediction using a novel Chinese benchmark.
Achieving Fair Medical Image Segmentation in Foundation Models with Adversarial Visual Prompt Tuning
Yuqi Li, Yanli Li, Kai Zhang, Fuyuan Zhang, Chuanguang Yang, Zhongliang Guo, Weiping Ding, Tingwen Huang
Information Sciences, 2025
A parameter-efficient adversarial visual prompt tuning method that mitigates demographic bias in foundation models for medical image segmentation while maintaining high performance.