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Beyond the Center: Exploring Anchor Box-Free Object Detection with CenterNet Object detection, a cornerstone of computer vision, has seen remarkable progress in recent years. While traditional methods rely heavily on anchor boxes to predict object locations and sizes, a novel approach called CenterNet has emerged, promising greater accuracy and efficiency by focusing solely on predicting the center point of objects. CenterNet, introduced by researchers at UC Berkeley, breaks away from the traditional paradigm by: Predicting Object Centers: Instead of directly predicting bounding boxes, CenterNet identifies the coordinates of the object's center point in each image. Heatmaps for Localization: It utilizes heatmaps to represent the probability of an object center existing at each location within the image. These heatmaps effectively capture...