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CenterNet is a significant breakthrough in anchor-free object detection, serving as the foundation for recent advanced detectors. This tutorial delves into the basics of CenterNet, explaining its operation using key points to represent objects and employing three heads for prediction. The model generates heat maps with exponential distance values, assigning high values at the object center that decrease exponentially with distance. Additionally, the video explores CenterNet's loss functions and compares different backbone architectures.
