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CenterNet revolutionizes anchor-free object detection and is the basis for recent state-of-the-art detectors. This video explains its fundamentals, including representing objects as key points and utilizing three heads for different predictions. The model outputs predictions based on input image dimensions and a model output stride. It uses key point heat maps with exponential distance assignment to determine object presence and class. Understanding CenterNet's workings and loss functions is crucial for object detection tasks.