Startseite Neuigkeiten Forschungsarbeiten Tutorials Datensätze Wiki SOTA LLM-Modelle GPU-Rangliste Veranstaltungen

Deutsch

Image Generation On Celeba 256X256

Metriken

bpd

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	bpd	Paper Title	Repository
SPN Menick and Kalchbrenner (2019)	0.61	Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling	-
LSGM	0.70	Score-based Generative Modeling in Latent Space	-
StyleSwin	-	StyleSwin: Transformer-based GAN for High-resolution Image Generation	-
NCP-VAE	-	A Contrastive Learning Approach for Training Variational Autoencoder Priors	-
MaCow (Unf)	0.95	MaCow: Masked Convolutional Generative Flow	-
Efficient-VDVAE	0.51	Efficient-VDVAE: Less is more	-
HiT-B	-	Improved Transformer for High-Resolution GANs	-
StyleALAE	-	Adversarial Latent Autoencoders	-
Glow (Kingma and Dhariwal, 2018)	1.03	Glow: Generative Flow with Invertible 1x1 Convolutions	-
Residual Flow	0.992	Residual Flows for Invertible Generative Modeling	-
Locally Masked PixelCNN	0.74	Locally Masked Convolution for Autoregressive Models	-
GLF+perceptual loss (ours)	-	Generative Latent Flow	-
MSP	-	Latent Space Factorisation and Manipulation via Matrix Subspace Projection	-
VQGAN	-	Taming Transformers for High-Resolution Image Synthesis	-
ANF Huang et al. (2020)	0.72	Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models	-
NVAE w/ flow	0.70	NVAE: A Deep Hierarchical Variational Autoencoder	-
MaCow (Var)	0.67	MaCow: Masked Convolutional Generative Flow	-

0 of 17 row(s) selected.