A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation
Few-shot semantic segmentation addresses the learning task in which only few images with ground truth pixel-level labels are available for the novel classes of interest. One is typically required to collect a large mount of data (i.e., base classes) with such ground truth information, followed by meta-learning strategies to address …