997 citations · 2.4k across the 65 of their papers we have counts for
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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…
Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Photo-realistic image restoration algorithms are typically evaluated by distortion measures (e.g., PSNR, SSIM) and by perceptual quality measures (e.g., FID, NIQE), where the desir…
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…
Still-Moving: Customized Video Generation without Customized Video Data
Hila Chefer, Shiran Zada, Roni Paiss +7
Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expan…
Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling
Noam Elata, Tomer Michaeli, Michael Elad
Compressed Sensing (CS) facilitates rapid image acquisition by selecting a small subset of measurements sufficient for high-fidelity reconstruction. Adaptive CS seeks to further en…
PSC: Posterior Sampling-Based Compression
Noam Elata, Tomer Michaeli, Michael Elad
Diffusion models have transformed the landscape of image generation and now show remarkable potential for image compression. Most of the recent diffusion-based compression methods…