52 citations · 73 across the 14 of their papers we have counts for
4 papers · 1 filter
Attribute Based Interpretable Evaluation Metrics for Generative Models
Dongkyun Kim, Mingi Kwon, Youngjung Uh
When the training dataset comprises a 1:1 proportion of dogs to cats, a generative model that produces 1:1 dogs and cats better resembles the training species distribution than ano…
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Yong-Hyun Park, Mingi Kwon, Jaewoong Choi +2
Despite the success of diffusion models (DMs), we still lack a thorough understanding of their latent space. To understand the latent space , we analy…
Training-free Content Injection using h-space in Diffusion Models
Jaeseok Jeong, Mingi Kwon, Youngjung Uh
Diffusion models (DMs) synthesize high-quality images in various domains. However, controlling their generative process is still hazy because the intermediate variables in the proc…
Unsupervised Discovery of Semantic Latent Directions in Diffusion Models
Yong-Hyun Park, Mingi Kwon, Junghyo Jo +1
Despite the success of diffusion models (DMs), we still lack a thorough understanding of their latent space. While image editing with GANs builds upon latent space, DMs rely on edi…