A Survey of Semantic Segmentation
It serves as a comprehensive resource for researchers and practitioners in computer vision by organizing existing knowledge on semantic segmentation.
This survey provides an overview of techniques for pixel-level semantic segmentation, covering traditional methods, recent convolutional neural network approaches, and evaluation metrics and datasets.
This survey gives an overview over different techniques used for pixel-level semantic segmentation. Metrics and datasets for the evaluation of segmentation algorithms and traditional approaches for segmentation such as unsupervised methods, Decision Forests and SVMs are described and pointers to the relevant papers are given. Recently published approaches with convolutional neural networks are mentioned and typical problematic situations for segmentation algorithms are examined. A taxonomy of segmentation algorithms is given.