Source Domain Subset Sampling for Semi-Supervised Domain Adaptation in Semantic Segmentation. (arXiv:2205.00312v2 [cs.CV] UPDATED)

In this paper, we introduce source domain subset sampling (SDSS) as a new
perspective of semi-supervised domain adaptation. We propose domain adaptation
by sampling and exploiting only a meaningful subset from source data for
training. Our key assumption is that the entire source domain data may contain
samples that are unhelpful for the adaptation. Therefore, the domain adaptation
can benefit from a subset of source data composed solely of helpful and
relevant samples. The proposed method effectively subsamples full source …

arxiv cv domain adaptation sampling segmentation semantic semi-supervised