Hi, I want to do experiment on dilated convolution. However, I have no time and GPUs to pre-trained on ImageNet. So I want to load pre-trained weights on ImageNet though they are common convolution which have 1 rate. From 3x3 common conv whilch has 1 rate to 3x3 dilated conv which has 2 rate, the numbers of parametres are same.
I have a try and it seems that dilated convolution can load weights successfully. However, the performance is very bad and the net cannot work normally. So I want to know, can I directly load pre-trained weights from common convolution to dilated convolution? It will cause some problem？Or just because there is no real pre-train on Imagenet, the performance is very poor.