I recently read this paper on the focal loss and there seem to be some contradictions in the paper. The first sentence of the conclusion is “In this work, we identify class imbalance as the primary obstacle preventing one-stage object detectors from surpassing top-performing, two-stage methods.”

However, when they used a simple weighting mechanism to balance the background and sought classes, the results were not significantly improved from using no weighting (alpha = 0.5), and when they employ their focal loss, they actually upweight background samples (alpha = 0.25). Is it not a misinterpretation of their results to say that their improvement comes from resolving a class imbalance?