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cs.CV2025

DarkHash: A Data-Free Backdoor Attack Against Deep Hashing

Ziqi Zhou, Menghao Deng, Yufei Song +6

Benefiting from its superior feature learning capabilities and efficiency, deep hashing has achieved remarkable success in large-scale image retrieval. Recent studies have demonstr…

cs.CV2025

Towards Real-World Deepfake Detection: A Diverse In-the-wild Dataset of Forgery Faces

Junyu Shi, Minghui Li, Junguo Zuo +8

Deepfakes, leveraging advanced AIGC (Artificial Intelligence-Generated Content) techniques, create hyper-realistic synthetic images and videos of human faces, posing a significant…

cs.CV2025

PB-UAP: Hybrid Universal Adversarial Attack For Image Segmentation

Yufei Song, Ziqi Zhou, Minghui Li +6

With the rapid advancement of deep learning, the model robustness has become a significant research hotspot, \ie, adversarial attacks on deep neural networks. Existing works primar…

cs.CV2024

Breaking Barriers in Physical-World Adversarial Examples: Improving Robustness and Transferability via Robust Feature

Yichen Wang, Yuxuan Chou, Ziqi Zhou +4

As deep neural networks (DNNs) are widely applied in the physical world, many researches are focusing on physical-world adversarial examples (PAEs), which introduce perturbations t…

cs.CV2024

NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors

Ziqi Zhou, Bowen Li, Yufei Song +6

With the advancement of deep learning, object detectors (ODs) with various architectures have achieved significant success in complex scenarios like autonomous driving. Previous ad…