features about rerank about self-similarity-grouping HOT 4 OPEN

Sorry for the late reply, I was really busy. Your understanding is right, we use re-rank between source feature and target feature. The motivation is to obtain a better re-rank result by the knowledge of source dataset. (since the model can achieve pretty good performance on source dataset).
e_dist is the euclidean distance among samples in a target dataset. r_dist is the distance after re-ranking.
Hope this can solve your problem.

from self-similarity-grouping.

I have also the same question.

from self-similarity-grouping.

same question too

from self-similarity-grouping.

Did you try to use the original dist rather than source dist? What's the performance compared to the current source dist?

from self-similarity-grouping.