INTRODUCTION
1.1 Contributions of this Survey
1.2 Relationship to Other Surveys
1.3 Organization
PRELIMINARY
2.1 Problem Statement
2.2 Taxonomy
2.3 Traditional Solutions
AUXILIARY INPUT-BASED IMAGE MATTING
3.1 Trimap-based Auxiliary Input
3.2 Pre-defined Auxiliary Input
3.3 User-interactive Auxiliary Input
3.4 Text-based Auxiliary Input
3.5 Summary
AUTOMATIC IMAGE MATTING
4.1 One-stage Matting Model
4.2 Sequential Matting Model
4.3 Encoder Sharing Model
4.4 Matting Target
4.5 Summary
IMAGE MATTING DATASETS
5.1 Synthetic Matting Datasets
5.2 Natural Matting Datasets
5.3 Summary
PERFORMANCE BENCHMARKING
6.1 Training Objectives
6.2 Evaluation Metrics
6.3 Results and Analysis
6.4 Model Complexity Analysis
APPLICATIONS
CHALLENGES AND OPPORTUNITIES
8.1 Challenges
8.2 Future Prospects
CONCLUSION