Unconditional Image Generation on CIFAR-10 (test)
1.54FIDGDD-I
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| GDD-INFE=12024.05 | 1.54 | 10.1 | — | — | |
| GDDNFE=12024.05 | 1.66 | 10.11 | — | — | |
| EDM-G++Space=Data, NFE=352022.11 | 1.77 | — | 2.55 | — | |
| CTMNFE=22024.05 | 1.87 | — | — | — | |
| PFGM++NFE=35, # param. (M)=55.72024.10 | 1.91 | — | — | — | |
| SiDNFE=1, alpha=1.22024.05 | 1.92 | 9.98 | — | — | |
| SiDNFE=1, # param. (M)=55.72024.10 | 1.92 | — | — | — | |
| LSGM-G++Space=Latent, NFE=1382022.11 | 1.94 | — | 3.42 | — | |
| EDMSpace=Data, NFE=35, Seed=manual2022.11 | 1.97 | — | 2.6 | — | |
| EDMNFE=35, # param. (M)=55.72024.10 | 1.97 | — | — | — | |
| EDMNFE=352024.05 | 1.98 | — | — | — | |
| CTMNFE=12024.05 | 1.98 | — | — | — | |
| SiDNFE=1, alpha=1.02024.05 | 2.02 | 10.01 | — | — | |
| EDMSpace=Data, NFE=39, Seed=random2022.11 | 2.03 | — | 2.6 | — | |
| TCMNFE=2, # param. (M)=55.7, Steps=2-step2024.10 | 2.05 | — | — | — | |
| LSGMSpace=Latent, NFE=1382022.11 | 2.1 | — | 3.43 | — | |
| LSGMNFE=147, # param. (M)=4752024.10 | 2.1 | — | — | — | |
| ECMNFE=2, # param. (M)=55.7, Steps=2-step2024.10 | 2.11 | — | — | — | |
| NCSN++Continuity Objective=continuous, SDE Type=VE, Architecture Depth=deep2020.11 | 2.2 | 9.89 | — | — | |
| NCSN++ cont.2021.07 | 2.2 | 9.89 | — | — | |
| NCSN++Space=Data, NFE=20002022.11 | 2.2 | — | 3.45 | — | |
| iCT-deepNFE=22024.05 | 2.24 | 9.89 | — | — | |
| iCT-deepNFE=2, # param. (M)=112, Steps=2-step2024.10 | 2.24 | — | — | — | |
| CLD-SGMSpace=Data, NFE=3122022.11 | 2.25 | — | 3.31 | — | |
| INDMSpace=Latent, NFE=20002022.11 | 2.28 | — | 3.09 | — | |
| NCSN++Continuity Objective=continuous, SDE Type=VE, Architecture Depth=standard2020.11 | 2.38 | 9.83 | — | — | |
| DDPM++Continuity Objective=continuous, SDE Type=VP, Architecture Depth=deep2020.11 | 2.41 | 9.68 | — | — | |
| DDPM++Continuity Objective=continuous, SDE Type=sub-VP, Architecture Depth=deep2020.11 | 2.41 | 9.57 | — | — | |
| NCSN++Continuity Objective=discrete, Architecture Depth=standard2020.11 | 2.45 | 9.73 | — | — | |
| iCTNFE=22024.05 | 2.46 | 9.8 | — | — | |
| TCMNFE=1, # param. (M)=55.7, Steps=1-step2024.10 | 2.46 | — | — | — | |
| iCTNFE=2, # param. (M)=56.4, Steps=2-step2024.10 | 2.46 | — | — | — | |
| Soft TruncationSpace=Data, NFE=20002022.11 | 2.47 | — | 2.91 | — | |
| iCT-deepNFE=12024.05 | 2.51 | 9.76 | — | — | |
| iCT-deepNFE=1, # param. (M)=112, Steps=1-step2024.10 | 2.51 | — | — | — | |
| DDPM++Continuity Objective=continuous, SDE Type=VP, Architecture Depth=standard2020.11 | 2.55 | 9.58 | — | — | |
| DDPM++Continuity Objective=continuous, SDE Type=sub-VP, Architecture Depth=standard2020.11 | 2.61 | 9.56 | — | — | |
| DMDNFE=12024.05 | 2.62 | — | — | — | |
| DDPM++Continuity Objective=discrete, Architecture Depth=standard2020.11 | 2.78 | 9.64 | — | — | |
| iCTNFE=12024.05 | 2.83 | 9.54 | — | — | |
| iCTNFE=1, # param. (M)=56.4, Steps=1-step2024.10 | 2.83 | — | — | — | |
| Improved DDPMloss=Lsimple2021.07 | 2.9 | — | — | — | |
| iDDPMSpace=Data, NFE=10002022.11 | 2.9 | — | 3.37 | — | |
| StyleGAN2-ADAMode=Unconditional2020.11 | 2.92 | 9.83 | — | — | |
| DDPM++ cont. (deep, sub-VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=sub-VP, Network Depth=Deep2020.11 | 2.92 | — | 2.99 | — | |
| DDPM++ cont2021.07 | 2.92 | — | 2.99 | — | |
| StyleGAN2-ADANFE=12024.05 | 2.92 | 9.82 | — | — | |
| CDNFE=22024.05 | 2.93 | — | — | — | |
| DDPM++ cont. (deep, VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=VP, Network Depth=Deep2020.11 | 3.08 | — | 3.13 | — | |
| DDPM++ cont. (sub-VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=sub-VP2020.11 | 3.16 | — | 3.02 | — | |
| Denoising Diffusion Probabilistic ModelsObjective=L_simple2020.06 | 3.17 | 9.46 | 3.75 | — | |
| DDPMMode=Unconditional2020.11 | 3.17 | 9.46 | — | — | |
| DDPM (Lsimple)Likelihood Type=ELBO, Training Objective=Discrete2020.11 | 3.17 | — | 3.75 | — | |
| DDPMloss=Lsimple2021.07 | 3.17 | 9.46 | — | — | |
| DDPMSpace=Data, NFE=10002022.11 | 3.17 | — | 3.75 | — | |
| DDPMNFE=10002024.05 | 3.17 | — | — | — | |
| DDPMNFE=1000, # param. (M)=35.72024.10 | 3.17 | — | — | — | |
| StyleGAN2 + ADA (v1)2020.06 | 3.26 | 9.74 | — | — | |
| StyleGAN2 + ADAAugmentation=Adaptive Discriminator Augmentation2021.07 | 3.26 | 9.74 | — | — | |
| TRACTNFE=2, # param. (M)=55.72024.10 | 3.32 | — | — | — | |
| DDPMLikelihood Type=Exact ODE Likelihood, Training Objective=Discrete2020.11 | 3.37 | — | 3.28 | — | |
| DeMe (After Merge)#Iterations=20Kx42024.10 | 3.51 | — | — | — | |
| CDNFE=12024.05 | 3.55 | — | — | — | |
| DDPM cont. (sub-VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=sub-VP2020.11 | 3.56 | — | 3.05 | — | |
| ECMNFE=1, # param. (M)=55.7, Steps=1-step2024.10 | 3.6 | — | — | — | |
| GENIENFEs=25, Score model checkpoint=Same, Striding schedule search=true2022.10 | 3.64 | — | — | — | |
| GENIENFEs=25, Score model checkpoint=Same, Striding schedule search=false2022.10 | 3.67 | — | — | — | |
| DDPM cont. (VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=VP2020.11 | 3.69 | — | 3.21 | — | |
| DMDNFE=1, # param. (M)=55.72024.10 | 3.77 | — | — | — | |
| DFNONFE=12024.05 | 3.78 | — | — | — | |
| DSNONFE=1, # param. (M)=65.82024.10 | 3.78 | — | — | — | |
| TRACTNFE=1, # param. (M)=55.72024.10 | 3.78 | — | — | — | |
| DeMe (Before Merge)#Iterations=20Kx42024.10 | 3.79 | — | — | — | |
| DDPM++ cont. (VP)Likelihood Type=Exact ODE Likelihood, Training Objective=Continuous, SDE Formulation=VP2020.11 | 3.93 | — | 3.16 | — | |
| GENIENFEs=20, Score model checkpoint=Same, Striding schedule search=true2022.10 | 3.94 | — | — | — | |
| GENIENFEs=20, Score model checkpoint=Same, Striding schedule search=false2022.10 | 3.94 | — | — | — | |
| DDIMDiffusion steps=1002021.06 | 4.16 | — | — | — | |
| DDIMNFE=1002024.05 | 4.16 | — | — | — | |
| ANT-UW#Iterations=80K2024.10 | 4.21 | — | — | — | |
| ANT-NashMTL#Iterations=80K2024.10 | 4.24 | — | — | — | |
| Learned SamplerNFEs=25, Score model checkpoint=Different, Striding schedule search=true2022.10 | 4.25 | — | — | — | |
| Uniform-Reflowtype=reflow2023.12 | 4.33 | — | — | — | |
| Distill-6-Reflowsteps=62023.12 | 4.35 | — | — | — | |
| Before-finetuning2024.10 | 4.42 | — | — | — | |
| Learned SamplerNFEs=25, Score model checkpoint=Different, Striding schedule search=false2022.10 | 4.47 | — | — | — | |
| GENIENFEs=15, Score model checkpoint=Same, Striding schedule search=true2022.10 | 4.49 | — | — | — | |
| GENIENFEs=15, Score model checkpoint=Same, Striding schedule search=false2022.10 | 4.49 | — | — | — | |
| Trun-SNR#Iterations=80K2024.10 | 4.49 | — | — | — | |
| S-PNDMNFEs=25, Score model checkpoint=Same2022.10 | 4.51 | — | — | — | |
| PDNFE=2, # param. (M)=602024.10 | 4.51 | — | — | — | |
| Diff-InstructNFE=1, # param. (M)=55.72024.10 | 4.53 | — | — | — | |
| StyleGAN2-D + ViTGAN-GDiscriminator=StyleGAN2, Generator=ViTGAN2021.07 | 4.57 | 9.89 | — | — | |
| Learned SamplerNFEs=20, Score model checkpoint=Different, Striding schedule search=true2022.10 | 4.72 | — | — | — | |
| F-PNDMNFEs=25, Score model checkpoint=Same2022.10 | 4.73 | — | — | — | |
| BOSS-6steps=62023.12 | 4.8 | — | — | — | |
| Ambient DataLoops (Loop 1)Corruption Type=JPEG, q=50, rho=1.2/2^32026.01 | 4.825 | — | — | — | |
| Learned SamplerNFEs=20, Score model checkpoint=Different, Striding schedule search=false2022.10 | 4.89 | — | — | — | |
| ViTGAN2021.07 | 4.92 | 9.69 | — | — | |
| Ambient DataLoops (Loop 1)Corruption Type=Blur, sigma_B=0.6, rho=1.2/2^32026.01 | 4.947 | — | — | — | |
| Ambient DataLoops (Loop 1)Corruption Type=Blur, sigma_B=0.8, rho=1.9/2^32026.01 | 5.044 | — | — | — |