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I'm studying the way keypoint detection is implemented in detectron2 compared to maskrcnn paper.
maskrcnn authors: "we minimize the cross-entropy loss over an m2 -way softmax output (which encourages a single point to be detected)"
but it looks like in detectron2 :
the loss is a simple cross entropy over the mask:
https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/roi_heads/keypoint_head.py#L88
And then the softmax is applied later only to get the keypoint score:
https://github.com/facebookresearch/detectron2/blob/main/detectron2/structures/keypoints.py#L218
Then there is slight discrepency with the paper, Am I correct ? Is there a reason ? Maybe it works better that way ?
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