You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
@yuhuayc For domain adaptation of detectors from the source domain to the target domain, we always train from the ImageNet pre-trained model. However, in practical application, the pre-trained model on the source domain is usually available. Why don't we fine-tune from the pre-trained model on the source domain model, but fine-tune from the ImageNet pre-trained model. The latter seems to take more time. Could you explain the reason for this?
The text was updated successfully, but these errors were encountered:
@BOBrown I think the reason why we choose to load the model pre-trained on ImageNet rather dataset-specific model is just for simplification. You can get enough semantic information from the existing ImageNet and that's what we need all. Of course, I think, maybe a dataset-specific model does result in a faster training process, but that should not be the research focus.
@yuhuayc For domain adaptation of detectors from the source domain to the target domain, we always train from the ImageNet pre-trained model. However, in practical application, the pre-trained model on the source domain is usually available. Why don't we fine-tune from the pre-trained model on the source domain model, but fine-tune from the ImageNet pre-trained model. The latter seems to take more time. Could you explain the reason for this?
The text was updated successfully, but these errors were encountered: