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CenterNet is a key player in anchor-free object detection, with recent state-of-the-art detectors built on its foundation. This tutorial delves into CenterNet's core concepts, explaining how it represents objects as key points and utilizes three heads for key point heat maps, local offsets, and object sizes. The model predicts object locations by assigning heat map values based on exponential distances from the object center. Understanding CenterNet's fundamentals and backbones is crucial for mastering object detection techniques.
