I have a pretrained net for semantic segmentation, which has been trained on the cityscapes dataset and its 19 classes (Person, car, traffic sign, …). One of those is "Person". I am only interested in this class.

Is it beneficial to retrain the model on the same dataset for just one class instead of 19?

If yes, what is a good strategy? Keep the weights for the feature extractors and just retrain the last classifying layer(s)? Or tune all the weights?

Thanks in advance!



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy