I. INTRODUCTION & MOTIVATION

II. TAXONOMY AND BACKGROUND  
A. Basic Image Data Augmentations

III. RESULTS  
A. Image Classification  
B. Object Detection  
C. Semantic Segmentation

IV. DISCUSSION AND FUTURE DIRECTIONS  
A. Current Approaches  
B. Theoretical Aspects  
C. Optimal Number of Samples Generation  
D. Selection of Data Augmentation Based on Model Architecture and Dataset  
E. Augmentations for Spaces  
F. Open Research Questions

V. CONCLUSION