Semantic Segmentation Pipeline

Semantic segmentation pipelines aim to automatically partition images or point clouds into semantically meaningful regions, a crucial task in various fields like robotics and remote sensing. Current research focuses on improving efficiency and accuracy through techniques like leveraging large pre-trained vision-language models, incorporating data augmentation and novel loss functions, and exploring unsupervised or weakly supervised learning methods to reduce reliance on expensive manual annotation. These advancements are driving progress in applications ranging from autonomous navigation and 3D scene reconstruction to precision agriculture and industrial quality control.