Image Reconstruction on CIFAR-10
0.0011LPIPSSI-Oracle
Evaluation results
| Method | Links | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| SI-OracleForward Model=Gaussian Blur (sigma_n = 0.25)2025.12 | 0.0011 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Motion Blur (sigma_n = 10^-6)2025.12 | 0.0026 | — | — | — | — | — | — | — | — | |
| SI-OracleForward Model=Motion Blur (sigma_n = 10^-6)2025.12 | 0.003 | — | — | — | — | — | — | — | — | |
| SI-OracleForward Model=Motion Blur (sigma_n = 0.1)2025.12 | 0.003 | — | — | — | — | — | — | — | — | |
| SI-OracleForward Model=Random Mask (sigma_n = 10^-6)2025.12 | 0.0044 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Random Mask (sigma_n = 10^-6)2025.12 | 0.0049 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Gaussian Blur (sigma_n = 0.1)2025.12 | 0.005 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Random Mask (sigma_n = 10^-6)2025.12 | 0.0051 | — | — | — | — | — | — | — | — | |
| SI-OracleForward Model=Gaussian Blur (sigma_n = 0.1)2025.12 | 0.0051 | — | — | — | — | — | — | — | — | |
| SI-OracleForward Model=Random Mask (sigma_n = 0.1)2025.12 | 0.0055 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Random Mask (sigma_n = 0.1)2025.12 | 0.0064 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Motion Blur (sigma_n = 10^-6)2025.12 | 0.0069 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Random Mask (sigma_n = 0.1)2025.12 | 0.0072 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Gaussian Blur (sigma_n = 0.1)2025.12 | 0.009 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Motion Blur (sigma_n = 0.1)2025.12 | 0.011 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Motion Blur (sigma_n = 0.1)2025.12 | 0.012 | — | — | — | — | — | — | — | — | |
| SCSIForward Model=Gaussian Blur (sigma_n = 0.25)2025.12 | 0.015 | — | — | — | — | — | — | — | — | |
| DPSForward Model=Gaussian Blur (sigma_n = 0.25)2025.12 | 0.025 | — | — | — | — | — | — | — | — | |
| LooCK x d*=256 x 42026.01 | 0.0285 | — | — | — | — | 19.22 | 0.988 | — | 34.51 | |
| LooCK x d*=32 x 42026.01 | 0.0435 | — | — | — | — | 24.53 | 0.9805 | — | 32.22 | |
| PQK x d*=256 x 4 x #322026.01 | 0.0953 | — | — | — | — | 27.15 | 0.9527 | — | 28.27 | |
| CVQ-VAEK x d*=1024 x 1282026.01 | 0.1883 | — | — | — | — | 24.73 | 0.8978 | — | 24.72 | |
| SQ-VAEK x d*=1024 x 1282026.01 | 0.2333 | — | — | — | — | 37.92 | 0.8779 | — | 24.07 | |
| VQ-VAEK x d*=1024 x 1282026.01 | 0.2504 | — | — | — | — | 39.67 | 0.8595 | — | 23.32 | |
| HVQ-VAEK x d*=1024 x 1282026.01 | 0.2553 | — | — | — | — | 41.08 | 0.8553 | — | 23.22 | |
| Basic Autoencoder (BAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.682 | — | — | — | — | — | — | — | |
| C-ViViTNumber of frames=8-frame2026.03 | — | — | — | — | — | 13.81 | — | — | 21.86 | |
| C-ViViTNumber of frames=18-frame2026.03 | — | — | — | — | — | 11.26 | — | — | 25.89 | |
| Cold Diffusiontask=desnowification2022.08 | — | — | 125.63 | 0.419 | 0.327 | 31.1 | 0.074 | 0.838 | — | |
| Denoising Autoencoder (DAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.229 | — | — | — | — | — | — | — | |
| DnCn2026.03 | — | — | — | — | — | — | 0.9709 | — | 38.68 | |
| Generative Autoencoder (GAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.574 | — | — | — | — | — | — | — | |
| HUMUS-Net2026.03 | — | — | — | — | — | — | 0.9873 | — | 42.25 | |
| LDA2026.03 | — | — | — | — | — | — | 0.9799 | — | 41.33 | |
| Meta2026.03 | — | — | — | — | — | — | 0.9626 | — | 38.11 | |
| Relational Autoencoder (RAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.281 | — | — | — | — | — | — | — | |
| Relational Denoising Autoencoder (RDAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.216 | — | — | — | — | — | — | — | |
| Relational Sparse Autoencoder (RSAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.292 | — | — | — | — | — | — | — | |
| Relational Variational Autoencoder (RVAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.417 | — | — | — | — | — | — | — | |
| Sparse Autoencoder (SAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.331 | — | — | — | — | — | — | — | |
| U-LDA2026.03 | — | — | — | — | — | — | 0.9875 | — | 43.21 | |
| U-MRI2026.03 | — | — | — | — | — | — | 0.9766 | — | 39.72 | |
| UNet2026.03 | — | — | — | — | — | — | 0.964 | — | 36.27 | |
| Variational Autoencoder (VAE)Validation Strategy=10-fold cross validation2018.02 | — | 0.552 | — | — | — | — | — | — | — | |
| VQVAENumber of frames=1-frame2026.03 | — | — | — | — | — | 24.53 | — | — | 19.97 |