Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey

arXiv:2403.01909v1 Announce Type: new
Abstract: Semantic segmentation is an important and popular research area in computer vision that focuses on classifying pixels in an image based on their semantics. However, supervised deep learning requires large amounts of data to train models and the process of labeling images pixel by pixel is time-consuming and laborious. This review aims to provide a first comprehensive and organized overview of the state-of-the-art research results on pseudo-label methods in the field of semi-supervised semantic segmentation, …

abstract arxiv computer computer vision cs.ai cs.cv data deep learning image images labeling labels pixel pixels popular process research segmentation semantic semantics semi-supervised survey train type vision