MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3263335
Abstract: Noisy labels, inevitably existing in pseudo-segmentation labels generated from weak object-level annotations, severely hamper model optimization for semantic segmentation. Previous works often rely on massive handcrafted losses and carefully tuned hyperparameters to resist noise, suffering… read more here.
Keywords: content aware; segmentation; model; meta net ... See more keywords