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This question is regarding YOLO v1 architecture as in here.

I am confused as to why authors have used 2 bounding boxes per grid cell for training. Assuming there can be only one object per grid cell. Would two boxes would be relevant?

If yes:

Then how would the target vector(y) for the grid cell containing the object centre look like? Wont this lead to repeated values of ground truth annotations for both bounding boxes?

else:

What is the exact rationale behind multiple bounding boxes?

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check this related question on another Stack Exchange site: Yolo v1 bounding boxes during training step, hope it will help you.

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