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Hello, since the Objectness loss (IoU in the case of YOLOX) should take into account all the predictions, not just the positives found with simOTA, how is it weighted the fact that uses all 13x13 + 26x26 + 52x52 predictions while reg_loss and class_loss use just positives ?
I can't even understand if it uses just the positives and their the IoU with respect to the assigned GT or if it uses also the negatives, how the target for the negative is calculated ? Thanks in advance for every answer.
The text was updated successfully, but these errors were encountered:
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Balancing factor in objectness
Objectness calculation and balancing factor w.r.t reg_loss and class_loss
Jul 1, 2024
Hello, since the Objectness loss (IoU in the case of YOLOX) should take into account all the predictions, not just the positives found with simOTA, how is it weighted the fact that uses all 13x13 + 26x26 + 52x52 predictions while reg_loss and class_loss use just positives ?
I can't even understand if it uses just the positives and their the IoU with respect to the assigned GT or if it uses also the negatives, how the target for the negative is calculated ? Thanks in advance for every answer.
The text was updated successfully, but these errors were encountered: