CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation. (arXiv:2112.05975v2 [cs.CV] UPDATED)

Acquiring the most representative examples via active learning (AL) can
benefit many data-dependent computer vision tasks by minimizing efforts of
image-level or pixel-wise annotations. In this paper, we propose a novel
Collaborative Panoptic-Regional Active Learning framework (CPRAL) to address
the semantic segmentation task. For a small batch of images initially sampled
with pixel-wise annotations, we employ panoptic information to initially select
unlabeled samples. Considering the class imbalance in the segmentation dataset,
we import a Regional Gaussian Attention module (RGA) to …

active learning arxiv collaborative cv learning segmentation semantic