1 Introduction  
1.1 Surveys on Semantic Segmentation  

2 Image Sets, Challenges and Performance Evaluation  
2.1 Image Sets and Challenges  
2.2 Performance Evaluation  

3 Before Fully Convolutional Networks  
3.1 Pre-Deep Learning Approaches  
3.2 Early Deep Learning Approaches  

4 Fully Convolutional Networks for Semantic Segmentation  

5 Post-FCN Approaches  
5.1 Techniques for Fine-grained Localization  
5.2 Scale-Invariance  
5.3 Object Detection-based Methods  
5.4 Evolution of Methods  

6 Future Scope and Potential Research Directions  
6.1 Weakly-Supervised Semantic Segmentation (WSSS)  
6.2 Zero-/Few-Shot Learning  
6.3 Domain Adaptation  
6.4 Real-Time Processing  
6.5 Contextual Information  

7 Conclusions