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CenterNet is a crucial advancement in anchor-free object detection, with recent top-performing detectors being based on it. This tutorial covers the fundamentals of CenterNet, explaining how it represents objects as key points and predicts bounding boxes. The model has three heads for key point heat maps, local offsets, and object sizes. Heat map values are assigned exponentially, with higher values near the object center. The video also compares different backbones used in CenterNet.
