the performance based on DECA and MICA
liushengtong-nreal opened this issue · 2 comments
liushengtong-nreal commented
In your paper table5 shows, why DECA-based methods lead to huge overfitting when using fine-tuning of partial layers or entire pipeline, but the MICA can get better performace? thanks
Zielon commented
I don't understand the question. If this is what you are asking, DECA needs more data to train.
liushengtong-nreal commented
Sorry, I didn't ask clearly. Why the red line get better performace than the blue line, but the green line get worse performance than the yellow line?
You state in your research that this may be due to fine-tuning of partial layers or entire pipeline leads to huge overfitting of the training data。Why does this happen to DECA but not to MICA?