I. INTRODUCTION  
A. Related Surveys  
B. Contributions and Organization  

II. VISUAL RECOGNITION: DATA TYPES, CHALLENGES AND PRELIMINARIES  
A. Data Types  
B. Challenges  
C. Preliminaries  

III. BEFORE RECOGNITION: EFFORTS ON THE DATA  
A. Data Compression  
B. Data Selection  
C. Data Representation  

IV. ON RECOGNITION: NETWORK COMPRESSION  
A. Compact Networks  
B. Tensor Decomposition  
C. Data Quantization  
D. Pruning  
E. Discussions and the Derived Joint Compression  

V. ON RECOGNITION: INFERENCE AND GENERALIZATION  
A. Fast Run-time Inference  
B. Generalization via Transfer Learning  

VI. SUMMARY AND DISCUSSIONS  
A. Summary of Recent Advances  
C. Unexplored Yet Promising New Directions