arXiv (Cornell University) · 2020 · 39 citations · 16 references
ComputingAutomotive EngineeringComputer ScienceAutonomous VehiclesComputer VisionMachine VisionDeep LearningObject DetectionObject RecognitionPattern RecognitionVehicle PerceptionAdversarial Detection RobustnessAdversarial ExamplesAdversarial SearchDetectorsDifferential RenderingObject Detection In Autonomous DrivingPhoto-realistic RenderingVehicle Detection
In this paper, we tackle the issue of physical adversarial examples for object detectors in the wild. Specifically, we proposed to generate adversarial patterns to be applied on vehicle surface so that it's not recognizable by detectors in the photo-realistic Carla simulator. Our approach contains two main techniques, an Enlarge-and-Repeat process and a Discrete Searching method, to craft mosaic-like adversarial vehicle textures without access to neither the model weight of the detector nor a differential rendering procedure. The experimental results demonstrate the effectiveness of our approach in the simulator.
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