IDs are 20160524\_GF2\_00133, 20161030\_GF1\_00153, 20161030\_GF1\_00036, 20160331\_NTU\_00007, and\
20161030\_GF2\_00071 for reproducing the result.

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   ![Straightforward object detection result on two training images. The model is trained on CARPK\_5\_5. The ground-truth bounding boxes are almost identical with the predicted boxes and thus are not shown for clarity. Confidence scores shown around each box are all close to 1 (0.8+). The threshold is 0.05, which means the confidence scores for unlabeled/undetected cars are less than 0.05. This is a clear indication of overfitting, which severely degrades the performance []{data-label="fig:overfitting_issue"}](figs/overfitting_20160524_GF2_00133.jpg "fig:"){width="0.48\linewidth"}   ![Straightforward object detection result on two training images. The model is trained on CARPK\_5\_5. The ground-truth bounding boxes are almost identical with the predicted boxes and thus are not shown for clarity. Confidence scores shown around each box are all close to 1 (0.8+). The threshold is 0.05, which means the confidence scores for unlabeled/undetected cars are less than 0.05. This is a clear indication of overfitting, which severely degrades the performance []{data-label="fig:overfitting_issue"}](figs/overfitting_20161030_GF1_00153.jpg "fig:"){width="0.48\linewidth"}
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### What if the unlabeled regions are treated as negative samples?

When the number of bounding boxes is decreased to 5, the mAP significantly drops to 4.40. To identify the reason, we evaluate the 