DETR Based Detector

DETR-based detectors are end-to-end object detection models utilizing transformer architectures to overcome limitations of traditional methods like reliance on hand-crafted anchors and non-maximum suppression. Current research focuses on improving DETR's efficiency and accuracy through techniques such as pre-training strategies, refined query designs (e.g., dynamic anchor boxes, positional queries), and knowledge distillation from teacher models. These advancements aim to enhance performance in challenging scenarios like dense object detection, rotated objects, and domain adaptation, ultimately impacting various applications including remote sensing, security inspection, and autonomous driving.