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Found 5 papers, 2 papers with code
PADetBench: Towards Benchmarking Physical Attacks against Object Detection
Moreover, physical dynamics and cross-domain transformation are challenging to strictly regulate in the real world, leading to unaligned evaluation and comparison, severely hindering the development of physically robust models.
A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking
Surprisingly, there has been a lack of comprehensive studies on the robustness of RS tasks, prompting us to undertake a thorough survey and benchmark on the robustness of image classification and object detection in RS.
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World
To further strengthen the attack performance, the adversarial patches are forced to be outside targets during training, by which the detected objects of interest, both on and outside patches, benefit the accumulation of attack efficacy.
Contextual adversarial attack against aerial detection in the physical world
We propose an innovative contextual attack method against aerial detection in real scenarios, which achieves powerful attack performance and transfers well between various aerial object detectors without smearing or blocking the interested objects to hide.
Benchmarking Adversarial Patch Against Aerial Detection
DNNs are vulnerable to adversarial examples, which poses great security concerns for security-critical systems.
