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20132023
most citedWorking Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding

128 citations · 329 across the 32 of their papers we have counts for

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Showing 2023 · cs.CVShow all

7 papers · 2 filters

cs.CV2023★ 2 cited

CLIPAG: Towards Generator-Free Text-to-Image Generation

Roy Ganz, Michael Elad

Perceptually Aligned Gradients (PAG) refer to an intriguing property observed in robust image classification models, wherein their input gradients align with human perception and p…

cs.CV2023★ 2 cited

Semi-supervised Quality Evaluation of Colonoscopy Procedures

Idan Kligvasser, George Leifman, Roman Goldenberg +2

Colonoscopy is the standard of care technique for detecting and removing polyps for the prevention of colorectal cancer. Nevertheless, gastroenterologists (GI) routinely miss appro…

cs.CV2023

Colonoscopy Coverage Revisited: Identifying Scanning Gaps in Real-Time

G. Leifman, I. Kligvasser, R. Goldenberg +2

Colonoscopy is the most widely used medical technique for preventing Colorectal Cancer, by detecting and removing polyps before they become malignant. Recent studies show that arou…

cs.CV2023

Nested Diffusion Processes for Anytime Image Generation

Noam Elata, Bahjat Kawar, Tomer Michaeli +1

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 ste…

cs.CV2023

Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems

Omer Belhasin, Yaniv Romano, Daniel Freedman +2

Uncertainty quantification for inverse problems in imaging has drawn much attention lately. Existing approaches towards this task define uncertainty regions based on probable value…

cs.CV2023★ 2 cited

Class-Conditioned Transformation for Enhanced Robust Image Classification

Tsachi Blau, Roy Ganz, Chaim Baskin +2

Robust classification methods predominantly concentrate on algorithms that address a specific threat model, resulting in ineffective defenses against other threat models. Real-worl…