Segmentation Annotation

Segmentation annotation, the process of labeling pixels in images to delineate objects or regions of interest, is crucial for training accurate image segmentation models. Current research focuses on improving annotation efficiency through techniques like self-supervised learning, semi-supervised learning leveraging limited labeled data, and innovative annotation paradigms such as point-wise labeling or utilizing satellite data for automated annotation of large datasets. These advancements address the significant cost and time constraints associated with manual annotation, enabling the development of more robust and accurate segmentation models across diverse applications, including medical image analysis, remote sensing, and robotics.