4 papers
Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation
Xiaofeng Cong, Jing Zhang, Yeying Jin +5
Underwater images often suffer from quality degradation due to absorption and scattering effects. Most existing underwater image enhancement algorithms produce a single, fixed-colo…
Improving Fast Adversarial Training via Self-Knowledge Guidance
Chengze Jiang, Junkai Wang, Minjing Dong +5
Adversarial training has achieved remarkable advancements in defending against adversarial attacks. Among them, fast adversarial training (FAT) is gaining attention for its ability…
Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective
Jie Gui, Chengze Jiang, Minjing Dong +4
While adversarial training is an effective defense method against adversarial attacks, it notably increases the training cost. To this end, fast adversarial training (FAT) is prese…
Unrevealed Threats: A Comprehensive Study of the Adversarial Robustness of Underwater Image Enhancement Models
Siyu Zhai, Zhibo He, Xiaofeng Cong +6
Learning-based methods for underwater image enhancement (UWIE) have undergone extensive exploration. However, learning-based models are usually vulnerable to adversarial examples s…