1 Introduction  
1.1 Comparison with Previous Reviews  
1.2 Scope  

2 Generic Object Detection  
2.2 Main Challenges  
2.3 Progress in the Past Two Decades  

3 A Brief Introduction to Deep Learning Feature Maps  

4 Datasets and Performance Evaluation  
4.1 Datasets  
4.2 Evaluation Criteria  

5 Detection Frameworks  
5.1 Region Based (Two Stage) Frameworks  
5.2 Unified (One Stage) Frameworks  

6 Object Representation  
6.1 Popular CNN Architectures  
6.2 Methods For Improving Object Representation  

7 Context Modeling  
7.1 Global Context  
7.2 Local Context  

8 Detection Proposal Methods  

9 Other Issues  

10 Discussion and Conclusion  
10.1 State of the Art Performance  
10.2 Summary and Discussion