Anchor Based Detector

Anchor-based object detectors, which utilize predefined bounding boxes (anchors) to locate objects in images, are a cornerstone of computer vision, but their performance is hampered by challenges like accurate label assignment and handling of small or oddly oriented objects. Current research focuses on improving anchor-based detectors by refining label assignment strategies (e.g., using similarity metrics beyond IoU), developing novel architectures that decouple and recouple bounding box predictions for better accuracy, and adapting them for specific applications such as autonomous driving and aerial imagery. These advancements enhance the accuracy and efficiency of object detection, impacting fields like autonomous driving, robotics, and medical image analysis.