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CenterNet is a groundbreaking anchor-free object detection model used in recent state-of-the-art detectors. This video tutorial explains how CenterNet works by representing objects as key points and utilizing three heads for key point heat maps, local offsets, and object sizes. The model predicts object locations based on input image dimensions and model output stride. The heat map values are exponential, with a value of 1 at the object center decreasing exponentially as it moves away. Understanding CenterNet fundamentals and comparing different backbones is crucial for object detection.
