A comprehensive comparison of alpha matting algorithms based on standardized performance metrics. This dataset provides researchers and developers with transparent benchmarking data to evaluate and compare different alpha matting approaches.
The algorithms are evaluated using four key metrics:
- SAD (Sum of Absolute Differences): Measures the absolute difference between predicted and ground truth alpha values. Lower values indicate better performance.
- MSE (Mean Squared Error): Calculates the average squared differences between predicted and ground truth values. Lower values indicate better performance.
- Gradient: Evaluates the preservation of edge information in the alpha matte. Lower values indicate better edge preservation.
- Connectivity Error: Measures the connectivity of the resulting alpha matte. Lower values indicate better connectivity preservation.
| Algorithm | SAD | MSE | Gradient | Connectivity Error |
|---|---|---|---|---|
| TransMatting | 3.1 | 2.3 | 2.8 | 6.2 |
| TMFNet | 3.4 | 4.0 | 3.9 | 15.0 |
| IamAlpha | 4.4 | 4.8 | 4.8 | 12.8 |
| LFPNet | 4.7 | 4.1 | 2.8 | 11.2 |
| TIMI-Net | 4.9 | 5.5 | 6.2 | 8.8 |
| SIM | 5.8 | 6.3 | 6.2 | 9.6 |
| PIIAMatting | 9.1 | 11.3 | 11.8 | 17.7 |
| HDMatt | 10.5 | 10.3 | 8.7 | 29.9 |
| AdaMatting | 12.6 | 12.8 | 12.3 | 22.3 |
| A2U Matting | 12.8 | 14.6 | 11.3 | 26.3 |
| SampleNet Matting | 13.0 | 13.2 | 14.2 | 25.4 |
| FGI Matting | 13.1 | - | - | - |
| GCA Matting | 14.2 | 14.5 | 12.8 | 21.7 |
| ATNet Matting | 15.4 | 14.9 | 18.1 | 24.9 |
| VDRN Matting | 15.8 | 17.4 | 18.7 | 22.4 |
| Deep Matting | 16.1 | 18.1 | 22.5 | 20.0 |
| Information-flow matting | 17.9 | 18.7 | 25.3 | 30.2 |
| IndexNet Matting | 19.3 | 22.0 | 17.6 | 24.7 |
| DCNN Matting | 20.0 | 19.2 | 23.7 | 26.7 |
| AlphaGAN | 20.9 | 23.2 | 22.4 | 35.8 |
| Context-aware Matting | 22.8 | 16.7 | 13.7 | 25.2 |
| Three-layer graph matting | 25.0 | 24.4 | 27.3 | 26.3 |
| ATPM Matting | 27.3 | 29.4 | 31.5 | 34.0 |
| Three Stages Matting | 28.5 | 25.7 | 31.4 | 25.9 |
| CSC Matting | 30.0 | 34.1 | 34.8 | 37.1 |
| LNSP Matting | 30.1 | 26.3 | 28.9 | 19.4 |
| Graph-based sparse matting | 31.1 | 30.7 | 28.1 | 40.0 |
| KL-Divergence Based Sparse Sampling | 31.2 | 29.8 | 28.2 | 40.0 |
| Patch-based Matting | 31.3 | 28.1 | 28.1 | 33.2 |
| TSPS-RV Matting | 32.6 | 31.6 | 35.4 | 31.5 |
| Iterative Transductive Matting | 33.2 | 37.1 | 41.3 | 50.0 |
| SVR Matting | 33.8 | 30.4 | 32.3 | 26.5 |
| Comprehensive sampling | 33.8 | 31.4 | 29.4 | 42.8 |
| Comprehensive Weighted Color and Texture | 34.3 | 32.2 | 34.4 | 37.8 |
| Sparse coded matting | 34.8 | 34.7 | 31.8 | 38.5 |
| LocalSamplingAndKnnClassification | 36.3 | 34.5 | 38.7 | 27.8 |
| Weighted Color and Texture Matting | 37.0 | 36.4 | 40.4 | 38.4 |
| CCM | 37.3 | 30.3 | 32.5 | 18.7 |
| LNCLM matting | 37.3 | 37.1 | 39.7 | 37.4 |
| Shared Matting | 37.5 | 37.5 | 33.5 | 37.7 |
| Global Sampling Matting | 39.8 | 36.3 | 32.8 | 34.5 |
| SRLO Matting | 40.8 | 42.5 | 42.6 | 46.3 |
| Segmentation-based matting | 41.1 | 40.4 | 32.6 | 34.3 |
| Improved color matting | 42.3 | 40.8 | 33.3 | 27.6 |
| KNN Matting | 42.6 | 37.5 | 44.3 | 33.9 |
| Local Spline Regression (LSR) | 42.7 | 44.0 | 44.2 | 28.9 |
| Global Sampling Matting (filter version) | 42.9 | 44.5 | 38.5 | 46.8 |
| Learning Based Matting | 44.0 | 43.7 | 43.3 | 30.8 |
| LMSPIR | 45.2 | 44.9 | 43.5 | 43.2 |
| Shared Matting (Real Time) | 45.6 | 47.0 | 48.5 | 45.5 |
| Closed-Form Matting | 46.0 | 44.6 | 44.1 | 19.2 |
| Improving Sampling Criterion | 49.7 | 41.6 | 42.5 | 34.2 |
| Cell-based matting Laplacian | 50.3 | 49.8 | 51.0 | 29.0 |
| Large Kernel Matting | 50.5 | 48.2 | 46.3 | 25.6 |
| Robust Matting | 51.2 | 49.6 | 45.3 | 45.0 |
| SPS matting | 53.3 | 44.5 | 40.7 | 42.1 |
| High-res matting | 54.2 | 51.5 | 46.9 | 35.3 |
| Transfusive Weights | 54.7 | 51.3 | 54.2 | 12.8 |
| Random Walk Matting | 57.9 | 57.4 | 55.5 | 8.7 |
| Geodesic Matting | 59.1 | - | - | 52.2 |
| Iterative BP Matting | 60.2 | - | - | 52.5 |
| Easy Matting | 60.6 | - | - | - |
| Improved Bayesian | 61.1 | - | - | - |
| Bayesian Matting | 62.4 | - | - | - |
| Poisson Matting | 64.8 | - | - | - |
- TransMatting - SAD: 3.1, MSE: 2.3
- TMFNet - SAD: 3.4, MSE: 4.0
- IamAlpha - SAD: 4.4, MSE: 4.8
- LFPNet - SAD: 4.7, MSE: 4.1
- TIMI-Net - SAD: 4.9, MSE: 5.5
- TransMatting - Gradient: 2.8
- LFPNet - Gradient: 2.8
- TMFNet - Gradient: 3.9
- TransMatting - Connectivity Error: 6.2
- TIMI-Net - Connectivity Error: 8.8
- Random Walk Matting - Connectivity Error: 8.7
- Some algorithms have incomplete metric data, indicated by "-" in the table
- Lower values indicate better performance across all metrics
- This comparison is based on standardized test datasets commonly used in alpha matting research
- Results may vary depending on specific use cases and image characteristics
- Data source: This comparison data was taken from imagematting.com
For detailed metric explanations and research context, see: Alpha Matting Evaluation Benchmark