Problem
The models provided in torchvision.models were trained on ImageNet so the size of image is (3, 224, 224). However, I have a small dataset (a custom dataset with about 20 thousand images) which is of smaller size.
I am wondering if there is anyway I could still use the pre-trained weights with those smaller images. There are two directions in my mind.

Modify the first layer and retrain that layer from scratch so that the the sizes of later layers are compatible with pre-trained weights.
Somehow augment the original images (perhaps some strategic padding) so that the size is made (224, 224).

However, both of them seems to be a long shot when moving into action.
Therefore, does anyone have encountered similar circumstances? Thank you in advance!