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Image Generation On Imagenet 512X512

Metrics

FID
Inception score

Results

Performance results of various models on this benchmark

Model Name
FID
Inception score
Paper TitleRepository
DiT-XL/23.04240.82Scalable Diffusion Models with Transformers-
MAR-L, Diff Loss1.73-Autoregressive Image Generation without Vector Quantization-
SIMS1.73-Self-Improving Diffusion Models with Synthetic Data-
EDM2- S Autoguidance (XS, T /16)1.34-Guiding a Diffusion Model with a Bad Version of Itself-
SiD-EDM2-M (498M)2.06-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
MAGVIT-v2 (w/o guidance)3.07213.1Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation-
Poly-INR3.81-Polynomial Implicit Neural Representations For Large Diverse Datasets-
SiDA-EDM2-M (498M)1.488-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
PaGoDA1.80-PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher-
SiDA-EDM2-L (777M)1.413-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
SiD-EDM2-XS (125M)3.353-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
MaskGIT (a=0.05)4.46342.0MaskGIT: Masked Generative Image Transformer-
MAGVIT-v21.91324.3Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation-
ADM-G7.72172.71Diffusion Models Beat GANs on Image Synthesis-
SiDA-EDM2-XL (1.1B)1.379-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
SiD-EDM2-S (280M)2.707-Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step-
TiTok-L-642.49-An Image is Worth 32 Tokens for Reconstruction and Generation-
DPC-U3.54350.2Discrete Predictor-Corrector Diffusion Models for Image Synthesis-
GMem1.71-GMem: A Modular Approach for Ultra-Efficient Generative Models-
Latent Diffusion (LDM-4-G)3.60247.67High-Resolution Image Synthesis with Latent Diffusion Models-
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Image Generation On Imagenet 512X512 | SOTA | HyperAI