Towards Formal Verification of Deep Neural Networks for Object Detection
The research extends formal verification methods, usually for image classification, to complex object detection models. It defines and verifies various adversarial attacks like misdetection and overdetection by casting them as logical constraints. The method uses a neural layer to model IoU values, successfully identifying unsafe instances across multiple datasets where other methods failed.