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CenterNet is a key anchor-free object detection model, serving as the foundation for recent state-of-the-art anchorless detectors. This video tutorial explores the fundamentals of CenterNet, explaining how it represents objects as key points and utilizes three heads for key point heat map, local offset, and object size prediction. The model outputs predictions based on input image dimensions and model output stride. Heat map values decrease exponentially from the object center, with C channels for object classes.
