1 INTRODUCTION
1.1 Domains of application
1.2 Structure of paper

2 SYNTHETIC DATA IN HUMAN ANALYSIS
2.1 Synthetic data
2.2 Data replacement versus Data enrichment
2.3 Benefits of synthetic data
2.4 Human analysis

3 HOW CAN SYNTHETIC DATASETS BE GENERATED?
3.1 Mathematical modelling
3.2 3D rendering tools
3.3 Input perturbations

4 HOW CAN SYNTHETIC DATA BE USED?
4.1 Simulating complex scenarios
4.2 Increasing the size and diversity of training dataset
4.4 Assessing scalability of systems
4.5 Providing annotated data for supervision
4.6 Pre-training a deep model
4.7 Fine-tuning a pre-trained model
4.8 Enforcing consistency regularization
4.9 Mitigating dataset bias and ensuring fairness

6 CHALLENGES AND DISCUSSION