# A Review on Deep Learning Techniques Applied to Semantic Segmentation

arXiv: https://arxiv.org/abs/1704.06857 · HTML: https://mlsanity.com/paper/1704.06857/

## Key facts

- Cited by 122 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2017.

## Built on by (most cited first, 30 of 122)

- [Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs](https://mlsanity.com/paper/2101.06894/) (2021)
- [Improving Generalization in Federated Learning by Seeking Flat Minima](https://mlsanity.com/paper/2203.11834/) (2022)
- [Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles](https://mlsanity.com/paper/2103.05121/) (2021)
- [Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems](https://mlsanity.com/paper/2106.14386/) (2021)
- [FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation](https://mlsanity.com/paper/2110.08988/) (2021)
- [PseudoClick: Interactive Image Segmentation with Click Imitation](https://mlsanity.com/paper/2207.05282/) (2022)
- [Semantic Ray: Learning a Generalizable Semantic Field with Cross-Reprojection Attention](https://mlsanity.com/paper/2303.13014/) (2023)
- [Generative Modeling of Turbulence](https://mlsanity.com/paper/2112.02548/) (2021)
- [GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting](https://mlsanity.com/paper/2411.07555/) (2024)
- [A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning](https://mlsanity.com/paper/2307.15092/) (2023)
- [Contrastive Gaussian Clustering: Weakly Supervised 3D Scene Segmentation](https://mlsanity.com/paper/2404.12784/) (2024)
- [OFFSEG: A Semantic Segmentation Framework For Off-Road Driving](https://mlsanity.com/paper/2103.12417/) (2021)
- [Eliminating Feature Ambiguity for Few-Shot Segmentation](https://mlsanity.com/paper/2407.09842/) (2024)
- [Deep Intellectual Property Protection: A Survey](https://mlsanity.com/paper/2304.14613/) (2023)
- [Denoising Diffusion Semantic Segmentation with Mask Prior Modeling](https://mlsanity.com/paper/2306.01721/) (2023)
- [Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Network](https://mlsanity.com/paper/2308.05605/) (2023)
- [Multi-modal Fusion Technology based on Vehicle Information: A Survey](https://mlsanity.com/paper/2211.06080/) (2022)
- [Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure](https://mlsanity.com/paper/2403.07292/) (2024)
- [Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision](https://mlsanity.com/paper/2312.15622/) (2023)
- [DDU-Net: Dual-Decoder-U-Net for Road Extraction Using High-Resolution Remote Sensing Images](https://mlsanity.com/paper/2201.06750/) (2022)
- [CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences -- Version 1](https://mlsanity.com/paper/2106.09757/) (2021)
- [An Informative Path Planning Framework for Active Learning in UAV-based Semantic Mapping](https://mlsanity.com/paper/2302.03347/) (2023)
- [Segment Anything Meets Semantic Communication](https://mlsanity.com/paper/2306.02094/) (2023)
- [SegTrans: Transferable Adversarial Examples for Segmentation Models](https://mlsanity.com/paper/2510.08922/) (2025)
- [Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance](https://mlsanity.com/paper/2211.10119/) (2022)
- [TrainSim: A Railway Simulation Framework for LiDAR and Camera Dataset Generation](https://mlsanity.com/paper/2302.14486/) (2023)
- [Using Semantic Information for Defining and Detecting OOD Inputs](https://mlsanity.com/paper/2302.11019/) (2023)
- [LuSNAR:A Lunar Segmentation, Navigation and Reconstruction Dataset based on Muti-sensor for Autonomous Exploration](https://mlsanity.com/paper/2407.06512/) (2024)
- [Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction](https://mlsanity.com/paper/2105.01456/) (2021)
- [Deep Leaning-Based Ultra-Fast Stair Detection](https://mlsanity.com/paper/2201.05275/) (2022)

## Abstract (arXiv)

Image semantic segmentation is more and more being of interest for computer vision and machine learning researchers. Many applications on the rise need accurate and efficient segmentation mechanisms: autonomous driving, indoor navigation, and even virtual or augmented reality systems to name a few. This demand coincides with the rise of deep learning approaches in almost every field or application target related to computer vision, including semantic segmentation or scene understanding. This paper provides a review on deep learning methods for semantic segmentation applied to various application areas. Firstly, we describe the terminology of this field as well as mandatory background concepts. Next, the main datasets and challenges are exposed to help researchers decide which are the ones that best suit their needs and their targets. Then, existing methods are reviewed, highlighting their contributions and their significance in the field. Finally, quantitative results are given for the described methods and the datasets in which they were evaluated, following up with a discussion of the results. At last, we point out a set of promising future works and draw our own conclusions about the state of the art of semantic segmentation using deep learning techniques.