Pose Transfer On Deep Fashion
Metriken
IS
SSIM
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | IS | SSIM |
|---|---|---|
| controllable-person-image-synthesis-with | 3.364 | 0.772 |
| upgpt-universal-diffusion-model-for-person | - | - |
| disentangled-person-image-generation | 3.228 | 0.614 |
| pose-guided-person-image-generation | 3.090 | 0.762 |
| deformable-gans-for-pose-based-human-image | 3.439 | 0.756 |
| dressing-in-order-recurrent-person-image | - | 0.806 |
| guided-image-to-image-translation-with-bi-1 | 3.22 | 0.767 |
| progressive-pose-attention-transfer-for | 3.209 | 0.773 |
| learning-flow-fields-in-attention-for | - | - |
| region-adaptive-texture-enhancement-for | 3.125 | 0.774 |
| xinggan-for-person-image-generation | 3.476 | 0.778 |
| bipartite-graph-reasoning-gans-for-person | 3.430 | 0.778 |