Anchor-free detection is a detection paradigm that abandons preset anchor boxes. The model directly predicts the absolute or relative coordinates of bounding boxes through network learning without relying on prior anchor boxes. It simplifies the model design and pre-training clustering process, reduces hyperparameters. The new generation of YOLO models gradually adopts this design to improve the model's generalization and simplicity.
