Search Results for author: Bahjat Kawar

Found 12 papers, 9 papers with code

Nested Diffusion Processes for Anytime Image Generation

1 code implementation30 May 2023 Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad

Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps.

Denoising Scheduling

GSURE-Based Diffusion Model Training with Corrupted Data

1 code implementation22 May 2023 Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad

Diffusion models have demonstrated impressive results in both data generation and downstream tasks such as inverse problems, text-based editing, classification, and more.

Editing Implicit Assumptions in Text-to-Image Diffusion Models

1 code implementation ICCV 2023 Hadas Orgad, Bahjat Kawar, Yonatan Belinkov

Our Text-to-Image Model Editing method, TIME for short, receives a pair of inputs: a "source" under-specified prompt for which the model makes an implicit assumption (e. g., "a pack of roses"), and a "destination" prompt that describes the same setting, but with a specified desired attribute (e. g., "a pack of blue roses").

Model Editing

Imagic: Text-Based Real Image Editing with Diffusion Models

no code implementations CVPR 2023 Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, Michal Irani

In this paper we demonstrate, for the very first time, the ability to apply complex (e. g., non-rigid) text-guided semantic edits to a single real image.

Style Transfer

Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance

1 code implementation18 Aug 2022 Bahjat Kawar, Roy Ganz, Michael Elad

In order to obtain class-conditional generation, it was suggested to guide the diffusion process by gradients from a time-dependent classifier.

Denoising Image Generation

Do Perceptually Aligned Gradients Imply Adversarial Robustness?

1 code implementation22 Jul 2022 Roy Ganz, Bahjat Kawar, Michael Elad

In this work, we focus on this trait and test whether \emph{Perceptually Aligned Gradients imply Robustness}.

Adversarial Robustness Image Classification

Threat Model-Agnostic Adversarial Defense using Diffusion Models

1 code implementation17 Jul 2022 Tsachi Blau, Roy Ganz, Bahjat Kawar, Alex Bronstein, Michael Elad

Deep Neural Networks (DNNs) are highly sensitive to imperceptible malicious perturbations, known as adversarial attacks.

Adversarial Defense Denoising

Denoising Diffusion Restoration Models

1 code implementation27 Jan 2022 Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song

Many interesting tasks in image restoration can be cast as linear inverse problems.

Colorization Deblurring +4

SNIPS: Solving Noisy Inverse Problems Stochastically

1 code implementation NeurIPS 2021 Bahjat Kawar, Gregory Vaksman, Michael Elad

In this work we introduce a novel stochastic algorithm dubbed SNIPS, which draws samples from the posterior distribution of any linear inverse problem, where the observation is assumed to be contaminated by additive white Gaussian noise.

Compressive Sensing Deblurring +2

Stochastic Image Denoising by Sampling from the Posterior Distribution

no code implementations23 Jan 2021 Bahjat Kawar, Gregory Vaksman, Michael Elad

Image denoising is a well-known and well studied problem, commonly targeting a minimization of the mean squared error (MSE) between the outcome and the original image.

Image Denoising

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