1 INTRODUCTION

2 RECOGNITION VS. RETRIEVAL

3 BACKGROUND: PROBLEM AND CHALLENGES

4 BENCHMARK DATASETS

5 FINE-GRAINED IMAGE RECOGNITION  
5.1 Recognition by Localization-Classification Subnetworks  
5.2 Recognition by End-to-End Feature Encoding  
5.3 Recognition with External Information  
5.4 Summary and Discussion  

6 FINE-GRAINED IMAGE RETRIEVAL  
6.1 Content-based Fine-Grained Image Retrieval  
6.2 Sketch-based Fine-Grained Image Retrieval  

7 COMMON TECHNIQUES SHARED BY BOTH FINE-GRAINED RECOGNITION AND RETRIEVAL

8 FUTURE DIRECTIONS

9 CONCLUSION