9 citations · 17 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 8 cited
An Edit Friendly DDPM Noise Space: Inversion and Manipulations
Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli
Denoising diffusion probabilistic models (DDPMs) employ a sequence of white Gaussian noise samples to generate an image. In analogy with GANs, those noise maps could be considered…
cs.CV2022★ 9 cited
SinDDM: A Single Image Denoising Diffusion Model
Vladimir Kulikov, Shahar Yadin, Matan Kleiner +1
Denoising diffusion models (DDMs) have led to staggering performance leaps in image generation, editing and restoration. However, existing DDMs use very large datasets for training…