title: Data augmentation for dense correspondence?
body: <p>I build a dataset by CAD software for dense correspondence task in computer vision. I trained on that data but got a severe overfitting. Then I used data augmentation, while the loss on validation set didn't decrease. I even 
  gradually increase the extent of data augmentation during the training, in other words, at first there is nearly no data augmentation, and the extent of augmentation kept increasing slowly during training, but still found it hard to decrease the validation loss. 
  Does it mean I need a model with more capacity?</p>