9 citations · 14 across the 5 of their papers we have counts for
6 papers
SP: Spherical Priors for Plug-and-Play Restoration
Sean Man, Ron Raphaeli, Matan Kleiner +1
In this paper, we introduce SP, a novel Plug-and-Play algorithm that accelerates maximum a posteriori image restoration by replacing denoisers with Spherical Encoders (SE) as g…
Illumination Angular Spectrum Encoding for Controlling the Functionality of Diffractive Networks
Matan Kleiner, Lior Michaeli, Tomer Michaeli
Diffractive neural networks have recently emerged as a promising framework for all-optical computing. However, these networks are typically trained for a single task, limiting thei…
FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models
Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas +1
Editing real images using a pre-trained text-to-image (T2I) diffusion/flow model often involves inverting the image into its corresponding noise map. However, inversion by itself i…
Coherence Awareness in Diffractive Neural Networks
Matan Kleiner, Lior Michaeli, Tomer Michaeli
Diffractive neural networks hold great promise for applications requiring intensive computational processing. Considerable attention has focused on diffractive networks for either…
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices
Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner +2
Text-to-image (T2I) diffusion models achieve state-of-the-art results in image synthesis and editing. However, leveraging such pretrained models for video editing is considered a m…
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…