Once upon a time I was fine-tuning the pretrained resnet for an image retrieval task and noticed that I got worse performance than using the pretrained vgg.
Recently I looked at another dataset paper, where they reported using off the shelf networks’ features as baselines, the result is that resnet is better than vgg, which is better than alexnet (makes sense). And I tried reproducing these baselines, succeeded with torchvision pretrained alexnet & vgg, but not resnet101. It’s supposed to be better than vgg, but it’s actually on par with alexnet only.
So now, I figure the problem lies with torchvision pretrained resnet? Maybe it’s not as good as Caffe’s or tensorflow’s model? Has somebody else released their own resnet models pretrained on Imagenet, that I can test