Hi,
from my understanding the memory module is a matrix which holds for each row the mean latent vector for each class (or - its centroid) over the source data. Later these centroids are also used to order the target data for a curriculum learning step.
What I don't understand is how the memory module is implemented for semantic segmentation. when there is a single class for each image the division to centroids is clear but what is your method when the labels are segmentation maps?
I did not find an explanation for this in the paper, or the code.
Hi, from my understanding the memory module is a matrix which holds for each row the mean latent vector for each class (or - its centroid) over the source data. Later these centroids are also used to order the target data for a curriculum learning step.
What I don't understand is how the memory module is implemented for semantic segmentation. when there is a single class for each image the division to centroids is clear but what is your method when the labels are segmentation maps?
I did not find an explanation for this in the paper, or the code.
Thanks, Nadav