# A Survey of Semantic Segmentation

arXiv: https://arxiv.org/abs/1602.06541 · HTML: https://mlsanity.com/paper/1602.06541/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2016.

## Built on by (most cited first, 30 of 30)

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- [Semantic Image Segmentation: Two Decades of Research](https://mlsanity.com/paper/2302.06378/) (2023)
- [HALSIE: Hybrid Approach to Learning Segmentation by Simultaneously Exploiting Image and Event Modalities](https://mlsanity.com/paper/2211.10754/) (2022)
- [Deep Image Matting: A Comprehensive Survey](https://mlsanity.com/paper/2304.04672/) (2023)
- [Weighted Intersection over Union (wIoU) for Evaluating Image Segmentation](https://mlsanity.com/paper/2107.09858/) (2021)
- [A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications](https://mlsanity.com/paper/2206.08672/) (2022)
- [Compensation Learning in Semantic Segmentation](https://mlsanity.com/paper/2304.13428/) (2023)
- [From Feature Importance to Natural Language Explanations Using LLMs with RAG](https://mlsanity.com/paper/2407.20990/) (2024)
- [Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges](https://mlsanity.com/paper/2304.05832/) (2023)
- [Class Similarity Transition: Decoupling Class Similarities and Imbalance from Generalized Few-shot Segmentation](https://mlsanity.com/paper/2404.05111/) (2024)
- [CLOI: An Automated Benchmark Framework For Generating Geometric Digital Twins Of Industrial Facilities](https://mlsanity.com/paper/2101.01355/) (2021)
- [Pavement Distress Detection and Segmentation using YOLOv4 and DeepLabv3 on Pavements in the Philippines](https://mlsanity.com/paper/2103.06467/) (2021)
- [MarsSeg: Mars Surface Semantic Segmentation with Multi-level Extractor and Connector](https://mlsanity.com/paper/2404.04155/) (2024)
- [GeloVec: Higher Dimensional Geometric Smoothing for Coherent Visual Feature Extraction in Image Segmentation](https://mlsanity.com/paper/2505.01057/) (2025)
- [Empirical Study of Multi-Task Hourglass Model for Semantic Segmentation Task](https://mlsanity.com/paper/2105.13531/) (2021)
- [Multi-Task Self-Supervised Learning for Image Segmentation Task](https://mlsanity.com/paper/2302.02483/) (2023)
- [Toward Flare-Free Images: A Survey](https://mlsanity.com/paper/2310.14354/) (2023)
- [A new baseline for edge detection: Make Encoder-Decoder great again](https://mlsanity.com/paper/2409.14976/) (2024)
- [A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation](https://mlsanity.com/paper/2502.05396/) (2025)
- [From Pixels to Damage Severity: Estimating Earthquake Impacts Using Semantic Segmentation of Social Media Images](https://mlsanity.com/paper/2507.02781/) (2025)
- [Expedition: A System for the Unsupervised Learning of a Hierarchy of Concepts](https://mlsanity.com/paper/2112.09348/) (2021)
- [Simulation of machine learning-based 6G systems in virtual worlds](https://mlsanity.com/paper/2204.09518/) (2022)
- [Global and Local Features through Gaussian Mixture Models on Image Semantic Segmentation](https://mlsanity.com/paper/2207.09162/) (2022)
- [Transferring learned patterns from ground-based field imagery to predict UAV-based imagery for crop and weed semantic segmentation in precision crop farming](https://mlsanity.com/paper/2210.11545/) (2022)
- [Lidar Annotation Is All You Need](https://mlsanity.com/paper/2311.04777/) (2023)
- [Satellite Captioning: Large Language Models to Augment Labeling](https://mlsanity.com/paper/2312.10905/) (2023)
- [More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation](https://mlsanity.com/paper/2402.06581/) (2024)
- [Towards In-Vehicle Multi-Task Facial Attribute Recognition: Investigating Synthetic Data and Vision Foundation Models](https://mlsanity.com/paper/2403.06088/) (2024)

## Abstract (arXiv)

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.