Hi,

First, thank you for sharing the exciting work.

I was trying to reproduce the results on MS COCO dataset based on my own training framework. When I used cross entropy loss loss_function=AsymmetricLoss(gamma_neg=0,** gamma_pos=0, clip=0) to achieve the baseline. The result (with backbone of ResNet101) of mAP ~82.5% was achieved, which is quite similar to the result reported in Fig. 8 of the paper.

Then, I replaced the loss function with loss_function=AsymmetricLoss(gamma_neg=4, gamma_pos=1, clip=0.05) -- all other hyper parameters were kept consistent. However, I only got the mAP result of ~82.1%.

Also, the traditional focal loss loss_function=AsymmetricLoss(gamma_neg=2, gamma_pos=2, clip=0) can not outperform the baseline (~82.5%), given the same configurations. I am curious about the issue of my training process.

Could you also please share some training tricks? For example, a snippet of code on adjusting learning rate, training transforms similar to that used for validation here, etc. Or, is there any suggestions?

Thank you.