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CenterNet is a key innovation in anchor-free object detection, with many state-of-the-art detectors based on it. Understanding CenterNet's fundamentals is crucial. The model represents objects as key points and predicts their bounding boxes. It has three heads for key point heat map, local offset, and object size. The heat map values decrease exponentially from the object center. Each object class has a dedicated channel in the heat map. The model's output size is determined by the input image's dimensions and the model's output stride.
