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Found 4 papers, 1 papers with code
Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability
With the advancement of generative models, the assessment of generated images becomes more and more important.
Similarity of Neural Architectures using Adversarial Attack Transferability
In recent years, many deep neural architectures have been developed for image classification.
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
Recently, video-based action recognition methods using convolutional neural networks (CNNs) achieve remarkable recognition performance.
Just One Moment: Structural Vulnerability of Deep Action Recognition against One Frame Attack
In this paper, we study the structural vulnerability of deep learning-based action recognition models against the adversarial attack using the one frame attack that adds an inconspicuous perturbation to only a single frame of a given video clip.
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