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Found 3 papers, 1 papers with code
Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks
Latency attacks against object detection represent a variant of adversarial attacks that aim to inflate the inference time by generating additional ghost objects in a target image.
Overload: Latency Attacks on Object Detection for Edge Devices
Our method is based on a newly formulated optimization problem and a novel technique, called spatial attention, to increase the inference time of object detection.
LTD: Low Temperature Distillation for Robust Adversarial Training
Despite the popularity of neural network models, a significant gap exists between the natural and robust accuracy of these models.
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