Detection Class

Detection class research focuses on improving the accuracy and efficiency of object detection systems, particularly in challenging scenarios like cross-domain adaptation and corner case detection in autonomous driving. Current efforts involve developing class-aware models, often employing teacher-student frameworks or multimodal learning approaches, to better handle variations in object appearance and improve generalization to unseen data. These advancements are crucial for enhancing the reliability and robustness of object detection in various applications, from medical image analysis to resource-constrained embedded systems.