Shiqu Liu

MatchMask: Mask-Centric Generative Data Augmentation for Label-Scarce Semantic Segmentation

Current semantic segmentation models are very data-hungry and require massive costly pixel-wise human annotations. Generative data augmentation, which scales the train set using generative models, provides a potential remedy. In this paper, we propose MatchMask, a novel mask-centric generative data