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cs.CV2026

Bridging Data Trials and Task Barriers: A Unified Framework for Sketch Biometric Identification

Decheng Liu, Bin Hu, Xinbo Gao +4

Different from existing cross-modality identification tasks (e.g., heterogeneous face recognition, sketch re-identification, etc.), we introduce a novel yet practical setting for t…

cs.CV2025

Improving Adversarial Robustness via Phase and Amplitude-aware Prompting

Yibo Xu, Dawei Zhou, Decheng Liu +1

Deep neural networks are found to be vulnerable to adversarial perturbations. The prompt-based defense has been increasingly studied due to its high efficiency. However, existing p…

cs.CV2025

A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation

Dawei Zhou, Suzhi Gang, Decheng Liu +3

Malicious applications of visual manipulation have raised serious threats to the security and reputation of users in many fields. To alleviate these issues, adversarial noise-based…

cs.CV2025

Towards Generalized Proactive Defense against Face Swapping with Contour-Hybrid Watermark

Ruiyang Xia, Dawei Zhou, Decheng Liu +4

Face swapping, recognized as a privacy and security concern, has prompted considerable defensive research. With the advancements in AI-generated content, the discrepancies between…

cs.CV2025

Structure-Accurate Medical Image Translation via Dynamic Frequency Balance and Knowledge Guidance

Jiahua Xu, Dawei Zhou, Lei Hu +3

Multimodal medical images play a crucial role in the precise and comprehensive clinical diagnosis. Diffusion model is a powerful strategy to synthesize the required medical images.…

cs.CV2024

AFD: Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement

Nuoyan Zhou, Dawei Zhou, Decheng Liu +2

Adversarial fine-tuning methods enhance adversarial robustness via fine-tuning the pre-trained model in an adversarial training manner. However, we identify that some specific late…