Ground Truth Box

Ground truth boxes represent the ideal, accurately labeled bounding boxes encompassing objects within an image, serving as the target for training object detection models. Current research focuses on improving the accuracy and efficiency of object detection by employing novel algorithms like diffusion models and optimal transport methods to refine predicted bounding boxes towards these ground truth targets, often within a multi-stage or iterative framework. These advancements aim to enhance the performance of object detection systems across various applications, including autonomous driving and visual grounding, by improving the precision and speed of object localization.