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most citedOpen-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixture

2 citations · 2 across the 1 of their papers we have counts for

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cs.CV20262 cited

Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixture

Chenqi Kong, Anwei Luo, Peijun Bao +5

Open-set face forgery detection poses significant security threats and presents substantial challenges for existing detection models. These detectors primarily have two limitations…

cs.CV2025

Active Adversarial Noise Suppression for Image Forgery Localization

Rongxuan Peng, Shunquan Tan, Xianbo Mo +2

Recent advances in deep learning have significantly propelled the development of image forgery localization. However, existing models remain highly vulnerable to adversarial attack…

cs.CV2024

Aligned Divergent Pathways for Omni-Domain Generalized Person Re-Identification

Eugene P. W. Ang, Shan Lin, Alex C. Kot

Person Re-identification (Person ReID) has advanced significantly in fully supervised and domain generalized Person R e ID. However, methods developed for one task domain transfer…

cs.CV2024

Diverse Deep Feature Ensemble Learning for Omni-Domain Generalized Person Re-identification

Eugene P. W. Ang, Shan Lin, Alex C. Kot

Person Re-identification (Person ReID) has progressed to a level where single-domain supervised Person ReID performance has saturated. However, such methods experience a significan…

cs.CV2024

A Unified Deep Semantic Expansion Framework for Domain-Generalized Person Re-identification

Eugene P. W. Ang, Shan Lin, Alex C. Kot

Supervised Person Re-identification (Person ReID) methods have achieved excellent performance when training and testing within one camera network. However, they usually suffer from…

cs.CV2024

Rethinking the Evaluation of Visible and Infrared Image Fusion

Dayan Guan, Yixuan Wu, Tianzhu Liu +2

Visible and Infrared Image Fusion (VIF) has garnered significant interest across a wide range of high-level vision tasks, such as object detection and semantic segmentation. Howeve…