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9.22k
Image Generation
FFHQ
StyleGAN2
https://arxiv.org/abs/1912.04958v2
Clean-FID (70k)
2.98
Image Generation
FFHQ
StyleGAN (no instance norm)
https://arxiv.org/abs/1904.06991v3
FID
4.16
Image Generation
FFHQ
StyleGAN
http://arxiv.org/abs/1812.04948v3
FID
4.42
Image Generation
FFHQ
StyleGAN
http://arxiv.org/abs/1812.04948v3
Clean-FID (70k)
4.77
Image Generation
FFHQ
StyleSwin
https://arxiv.org/abs/2112.10762v2
FID
5.07
Image Generation
FFHQ
HiT-B
https://arxiv.org/abs/2106.07631v3
FID
6.37
Image Generation
FFHQ
StyleGAN2
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
10.8309
Image Generation
FFHQ
StyleGAN2
https://arxiv.org/abs/2103.01209v4
Clean-FID (70k)
2.98
Image Generation
FFHQ
MSG-StyleGAN
https://arxiv.org/abs/1903.06048v4
Clean-FID (70k)
6.51
Image Generation
FFHQ
GANsformer
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
12.8478
Image Generation
FFHQ
GAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
13.1844
Image Generation
FFHQ
SAGAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
16.2069
Image Generation
FFHQ
VQGAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
63.1165
Image Generation
AFHQ Wild
Vision-aided GAN
https://arxiv.org/abs/2112.09130v3
clean-KID
0.38 ± .02
Image Generation
AFHQ Wild
Vision-aided GAN
https://arxiv.org/abs/2112.09130v3
clean-FID
2.35 ± .02
Image Generation
AFHQ Wild
Vision-aided GAN
https://arxiv.org/abs/2112.09130v3
FID
2.25
Image Generation
AFHQ Wild
StyleGAN2-ADA
https://arxiv.org/abs/2006.06676v2
clean-KID
0.44 ± .01
Image Generation
AFHQ Wild
StyleGAN2-ADA
https://arxiv.org/abs/2006.06676v2
clean-FID
3.00 ± .01
Image Generation
AFHQ Wild
StyleGAN2-ADA
https://arxiv.org/abs/2006.06676v2
FID
3.05
Image Generation
AFHQ Wild
Diffusion InsGen
https://arxiv.org/abs/2206.02262v4
FID
1.51
Image Generation
AFHQ Wild
Projected GAN
https://arxiv.org/abs/2111.01007v1
FID
2.17
Image Generation
AFHQ Wild
Stylegan2-ada (NVIDIA pre-trained)
https://arxiv.org/abs/2203.03226v3
RMSE Signature
33306
Image Generation
AFHQ Wild
Stylegan2-ada (NVIDIA pre-trained)
https://arxiv.org/abs/2203.03226v3
RMSE log-signature
26622
Image Generation
AFHQ Wild
Stylegan2-ada (NVIDIA pre-trained)
https://arxiv.org/abs/2203.03226v3
MAE Signature
25578
Image Generation
AFHQ Wild
Stylegan2-ada (NVIDIA pre-trained)
https://arxiv.org/abs/2203.03226v3
MAE log-signature
20359
Image Generation
CIFAR-10 (10% data)
DiffAugment-StyleGAN2
https://arxiv.org/abs/2006.10738v4
FID
14.5
Image Generation
CIFAR-10 (10% data)
DiffAugment-CR-BigGAN
https://arxiv.org/abs/2006.10738v4
FID
18.7
Image Generation
CIFAR-10 (10% data)
DiffAugment-BigGAN
https://arxiv.org/abs/2006.10738v4
FID
22.4
Image Generation
Binarized MNIST
CR-NVAE
https://arxiv.org/abs/2105.14859v2
nats
76.93
Image Generation
Binarized MNIST
Locally Masked PixelCNN (8 orders)
https://arxiv.org/abs/2006.12486v3
bits/dimension
0.143
Image Generation
Binarized MNIST
Locally Masked PixelCNN (8 orders)
https://arxiv.org/abs/2006.12486v3
nats
77.58
Image Generation
Binarized MNIST
BFN
https://arxiv.org/abs/2308.07037v5
nats
77.87
Image Generation
Binarized MNIST
Efficient-VDVAE
https://arxiv.org/abs/2203.13751v2
nats
79.09
Image Generation
Binarized MNIST
PixelRNN
http://arxiv.org/abs/1601.06759v3
nats
79.20
Image Generation
Binarized MNIST
PixelCNN
http://arxiv.org/abs/1601.06759v3
nats
81.30
Image Generation
Binarized MNIST
EoNADE-5 2hl (128 orders)
http://arxiv.org/abs/1406.1485v3
nats
84.68
Image Generation
Binarized MNIST
EoNADE 2hl (128 orders)
http://papers.nips.cc/paper/5277-iterative-neural-autoregressive-distribution-estimator-nade-k
nats
85.10
Image Generation
Binarized MNIST
MADE 2hl (32 orders)
http://arxiv.org/abs/1502.03509v2
nats
86.64
Image Generation
Binarized MNIST
NADE
http://arxiv.org/abs/1310.1757v2
nats
88.33
Image Generation
iNaturalist 2019
StyeGAN2 + NoisyTwins
https://arxiv.org/abs/2304.05866v1
FID
11.46
Image Generation
iNaturalist 2019
BigGAN + gSR
https://arxiv.org/abs/2208.09932v1
FID
13.95
Image Generation
Pokemon 1024x1024
StyleGAN-XL
https://arxiv.org/abs/2202.00273v2
FID
25.47
Image Generation
Pokemon 1024x1024
Projected GAN
https://arxiv.org/abs/2111.01007v1
FID
33.96
Image Generation
Pokemon 1024x1024
FastGAN
https://arxiv.org/abs/2101.04775v1
FID
56.46
Image Generation
CelebA-HQ 128x128
U-Net GAN
https://arxiv.org/abs/2002.12655v2
FID
2.03
Image Generation
CelebA-HQ 128x128
U-Net GAN
https://arxiv.org/abs/2002.12655v2
Inception score
3.33
Image Generation
CelebA-HQ 128x128
COCO-GAN
https://arxiv.org/abs/1904.00284v4
FID
5.74
Image Generation
CelebA-HQ 128x128
PA-GAN
https://arxiv.org/abs/1901.10422v3
FID
15.4
Image Generation
CelebA-HQ 128x128
CR+LT-SNDCGAN
https://arxiv.org/abs/2010.09893v1
FID
16.84
Image Generation
CelebA-HQ 128x128
CR-GAN
https://arxiv.org/abs/1910.12027v2
FID
16.97
Image Generation
CelebA-HQ 128x128
SS-GAN (sBN)
http://arxiv.org/abs/1811.11212v2
FID
24.36
Image Generation
CelebA-HQ 128x128
QSNGAN
https://arxiv.org/abs/2104.09630v2
FID
29.417
Image Generation
CelebA-HQ 128x128
QSNGAN
https://arxiv.org/abs/2104.09630v2
IS
2.249
Image Generation
1,078 People 3D Faces Collection Data
Sessiz çığlık
https://arxiv.org/abs/2202.00708v3
10%
15
Image Generation
Cityscapes
Projected GAN
https://arxiv.org/abs/2111.01007v1
FID-10k-training-steps
3.41
Image Generation
Cityscapes
GANformer
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
5.7589
Image Generation
Cityscapes
StyleGAN2
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
8.35
Image Generation
Cityscapes
GAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
11.5652
Image Generation
Cityscapes
SAGAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
12.8077
Image Generation
Cityscapes
VQGAN
https://arxiv.org/abs/2103.01209v4
FID-10k-training-steps
173.7971
Image Generation
FFHQ 128 x 128
DDPM-IP
https://arxiv.org/abs/2301.11706v3
FID
2.98
Image Generation
FFHQ 128 x 128
Anycost GAN
https://arxiv.org/abs/2103.03243v1
FID
3.98
Image Generation
FFHQ 128 x 128
LadaGAN
https://arxiv.org/abs/2401.09596v4
FID
4.48
Image Generation
CelebA
FInCFlow
https://arxiv.org/abs/2301.09266v1
bpd (8-bits)
null
Image Generation
MNIST
Locally Masked PixelCNN (8 orders)
https://arxiv.org/abs/2006.12486v3
bits/dimension
0.65
Image Generation
MNIST
Residual Flow
https://arxiv.org/abs/1906.02735v6
bits/dimension
0.97
Image Generation
MNIST
RNODE
https://arxiv.org/abs/2002.02798v3
bits/dimension
0.97
Image Generation
MNIST
MintNet
https://arxiv.org/abs/1907.07945v2
bits/dimension
0.98
Image Generation
MNIST
i-ResNet
https://arxiv.org/abs/1811.00995v3
bits/dimension
1.06
Image Generation
MNIST
Sliced Iterative Generator
https://arxiv.org/abs/2007.00674v3
bits/dimension
1.34
Image Generation
MNIST
Sliced Iterative Generator
https://arxiv.org/abs/2007.00674v3
FID
4.5
Image Generation
MNIST
PR-GLOW- Recall
null
FID
4.45
Image Generation
MNIST
PR-GLOW- Recall
null
Precision
0.77
Image Generation
MNIST
PR-GLOW- Recall
null
Recall
0.72
Image Generation
MNIST
GLF+perceptual loss (ours)
https://arxiv.org/abs/1905.10485v2
FID
5.8
Image Generation
MNIST
HypGAN
https://arxiv.org/abs/2102.05567v1
FID
7.87
Image Generation
MNIST
JKO-iFlow
null
FID
7.95
Image Generation
MNIST
PR-GLOW- Precision
null
FID
12.884
Image Generation
MNIST
PR-GLOW- Precision
null
Precision
0.832
Image Generation
MNIST
PR-GLOW- Precision
null
Recall
0.6509
Image Generation
MNIST
Spiking-Diffusion
https://arxiv.org/abs/2308.10187v4
FID
27.61
Image Generation
MNIST
Spiking-Diffusion
https://arxiv.org/abs/2308.10187v4
Precision
0.83
Image Generation
MNIST
Spiking-Diffusion
https://arxiv.org/abs/2308.10187v4
Recall
0.65
Image Generation
MNIST
Feature Alignment
https://arxiv.org/abs/2106.12562v2
FID
37.50
Image Generation
MNIST
PresGAN
https://arxiv.org/abs/1910.04302v1
FID
38.53
Image Generation
MNIST
Transition Matrix
https://www.mdpi.com/2227-7390/12/7/1024
SSIM
0.697
Image Generation
MNIST
Transition Matrix
https://www.mdpi.com/2227-7390/12/7/1024
PSNR
17.94
Image Generation
CelebA-HQ 64x64
COCO-GAN
https://arxiv.org/abs/1904.00284v4
FID
4.0
Image Generation
CelebA-HQ 64x64
VAEBM
https://arxiv.org/abs/2010.00654v3
FID
5.31
Image Generation
CelebA-HQ 64x64
QA-GAN
https://arxiv.org/abs/1911.03149v1
FID
6.42
Image Generation
ImageNet 256x256 - 1 labeled data per class
DPT
null
FID-50k
4.00
Image Generation
ImageNet 256x256 - 1 labeled data per class
DPT
null
sFID
6.56
Image Generation
ImageNet 256x256 - 1 labeled data per class
DPT
null
IS
178.05
Image Generation
ImageNet 256x256 - 1 labeled data per class
DPT
null
Precision
0.81
Image Generation
ImageNet 256x256 - 1 labeled data per class
DPT
null
Recall
0.53
Image Generation
KMNIST
Spiking-Diffusion
https://arxiv.org/abs/2308.10187v4
FID
59.23
Image Generation
CAT 256x256
StyleGAN2 + DA + RLC (Ours)
https://arxiv.org/abs/2104.03310v1
FID
10.16
Image Generation
CAT 256x256
RaSGAN
http://arxiv.org/abs/1807.00734v3
FID
32.11
Image Generation
CAT 256x256
WGAN-GP
http://arxiv.org/abs/1704.00028v3
FID
155.46
Image Generation
ADE-Indoor
Projected GAN
https://arxiv.org/abs/2111.01007v1
FID
6.7