Table 3.
Results of different state-of-the-art methods for fashion parsing [68]
| Model | Market-1501 [104] | DeepFashion [43] | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SSIM | IS | Mask-SSIM | Mask-IS | DS | pSSIM | SSIM | IS | DS | pSSIM | |
| PG2 [48] | 0.261 | 3.495 | 0.782 | 3.367 | 0.390 | – | 0.773 | 3.163 | 0.951 | – |
| Def-GAN [72] | 0.291 | 3.230 | 0.807 | 3.502 | 0.720 | – | 0.760 | 3.362 | 0.976 | – |
| PATN [91] | 0.81 | 3.162 | 0.799 | 3.737 | 0.796 | 0.6186 | 0.771 | 3.201 | 0.976 | 0.799 |
| Loss function [68] | 0.312 | 3.326 | 0.810 | 3.807 | 0.742 | 0.6415 | 0.776 | 3.262 | 0.982 | 0.813 |
| Real Data | 1.000 | 3.890 | 1.000 | 3.706 | 0.740 | 1 | 1.000 | 4.053 | 0.968 | 1 |