Image Generation on Standard Cars
8.93FIDSADM (full)
Evaluation results
| Method | Links | |
|---|---|---|
| SADM (full)Pre-training=ImageNet, Resolution=256x256, Tuning Strategy=Full Fine-tuning2024.02 | 8.93 | |
| SADM (parameter-efficient)Pre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 9.26 | |
| Full Fine-tuning with DDPMPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Full Fine-tuning2024.02 | 9.79 | |
| DiffFitPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 9.9 | |
| BitFitPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 10.64 | |
| AdaptFormerPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 10.73 | |
| VPTPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 22.12 | |
| LoRAPre-training=ImageNet, Resolution=256x256, Tuning Strategy=Parameter-efficient2024.02 | 76.24 |