Landmark Regression on MAFL (test)
2.36MSE (%)DLP++ (with learned features)
Evaluation Results
| Method | Links | |
|---|---|---|
| DLP++ (with learned features)K=302022.05 | 2.36 | |
| DLP++ (with learned features)K=502022.05 | 2.39 | |
| DLP+ (with log-variance)K=502022.05 | 2.42 | |
| DLP++ (with learned features)K=252022.05 | 2.42 | |
| Deep Latent Particles (DLP)K=502022.05 | 2.43 | |
| DLP+ (with log-variance)K=302022.05 | 2.49 | |
| DLP+ (with log-variance)K=252022.05 | 2.52 | |
| KeyNetSupervision=Unsupervised, K=502022.05 | 2.54 | |
| Deep Latent Particles (DLP)K=302022.05 | 2.56 | |
| KeyNetSupervision=Unsupervised, K=302022.05 | 2.58 | |
| DundarSupervision=Unsupervised, K=102022.05 | 2.76 | |
| Deep Latent Particles (DLP)K=252022.05 | 2.87 | |
| DLP++ (with learned features)K=102022.05 | 2.98 | |
| DLP+ (with log-variance)K=102022.05 | 3.12 | |
| ZhangSupervision=Unsupervised, K=302022.05 | 3.16 | |
| KeyNetSupervision=Unsupervised, K=102022.05 | 3.19 | |
| LorenzSupervision=Unsupervised, K=102022.05 | 3.24 | |
| WilesSupervision=Unsupervised2022.05 | 3.44 | |
| ZhangSupervision=Unsupervised, K=102022.05 | 3.46 | |
| Deep Latent Particles (DLP)K=102022.05 | 3.87 | |
| MTCNNSupervision=Supervised2022.05 | 5.39 | |
| ShuSupervision=Unsupervised2022.05 | 5.45 | |
| Thewlis (frames)Supervision=Unsupervised2022.05 | 5.83 | |
| ThewlisSupervision=Unsupervised, K=502022.05 | 6.67 | |
| ThewlisSupervision=Unsupervised, K=302022.05 | 7.15 | |
| TCDCNSupervision=Supervised2022.05 | 7.95 | |
| Cascaded CNNSupervision=Supervised2022.05 | 9.73 | |
| CFANSupervision=Supervised2022.05 | 15.84 |