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Image Generation On Celeba Hq 256X256

Métriques

FID

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	FID	Paper Title	Repository
LFM	5.26	Flow Matching in Latent Space
DC-VAE	15.81	Dual Contradistinctive Generative Autoencoder	-
UNCSN++ (RVE) + ST	7.16	Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
VAEBM	20.38	VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
RDUOT	5.6	A High-Quality Robust Diffusion Framework for Corrupted Dataset
DDGAN	7.64	Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
WaveDiff	5.94	Wavelet Diffusion Models are fast and scalable Image Generators
LDM-4	5.11	High-Resolution Image Synthesis with Latent Diffusion Models
DDMI	8.73	DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
VQGAN+Transformer	10.2	Taming Transformers for High-Resolution Image Synthesis
BOSS	-	Bellman Optimal Stepsize Straightening of Flow-Matching Models
RDM	3.15	Relay Diffusion: Unifying diffusion process across resolutions for image synthesis
Dual-MCMC EBM	15.89	Learning Energy-based Model via Dual-MCMC Teaching	-
StyleSwin	3.25	StyleSwin: Transformer-based GAN for High-resolution Image Generation
LSGM	7.22	Score-based Generative Modeling in Latent Space
Joint-EBM	9.89	Learning Joint Latent Space EBM Prior Model for Multi-layer Generator	-
RNODE	-	How to train your neural ODE: the world of Jacobian and kinetic regularization
Diffusion-JEBM	8.78	Learning Latent Space Hierarchical EBM Diffusion Models	-
GLOW	68.93	Glow: Generative Flow with Invertible 1x1 Convolutions

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