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Found 3 papers, 2 papers with code
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks
Human motion prediction is still an open problem, which is extremely important for autonomous driving and safety applications.
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
Human motion prediction is still an open problem extremely important for autonomous driving and safety applications.
WSAM: Visual Explanations from Style Augmentation as Adversarial Attacker and Their Influence in Image Classification
Currently, style augmentation is capturing attention due to convolutional neural networks (CNN) being strongly biased toward recognizing textures rather than shapes.
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