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홈
SOTA
이미지 생성
Image Generation On Ffhq 256 X 256
Image Generation On Ffhq 256 X 256
평가 지표
FID
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
FID
Paper Title
Repository
Efficient-VDVAE
34.88
Efficient-VDVAE: Less is more
Efficient-vdVAE (Exposing)
34.88
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
VE (erel=0.01)
15.67
Gotta Go Fast When Generating Data with Score-Based Models
VE (erel=0.02)
15.67
Gotta Go Fast When Generating Data with Score-Based Models
BigGAN
11.48
A U-Net Based Discriminator for Generative Adversarial Networks
VQGAN+Transformer
9.6
Taming Transformers for High-Resolution Image Synthesis
Unleash-Trans (Exposing)
9.02
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
LDM
8.11
-
-
LDM (Exposing)
8.11
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
GANFormer2
7.77
Compositional Transformers for Scene Generation
-
U-Net GAN
7.48
A U-Net Based Discriminator for Generative Adversarial Networks
GANFormer
7.42
Generative Adversarial Transformers
Unleashing Transformers
6.11
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
UDM (RVE) + ST
5.54
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
StyleGAN2-ada (Exposing)
5.30
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
SWAGAN-Bi
5.22
SWAGAN: A Style-based Wavelet-driven Generative Model
INR-GAN-bil
4.95
Adversarial Generation of Continuous Images
LFM
4.55
Flow Matching in Latent Space
CIPS
4.38
Image Generators with Conditionally-Independent Pixel Synthesis
Projected-GAN (Exposing)
4.29
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
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