Color Image Enhancement by a Forward-and-Backward Adaptive Beltrami Flow. - Nir A. Sochen; Guy Gilboa; Yehoshua Y. Zeevi (AFPAC, 2000)

Signal and image enhancement by a generalized forward-and-backward adaptive diffusion process. - Guy Gilboa; Yehoshua Y. Zeevi; Nir A. Sochen (EUSIPCO, 2000)

Anisotropic selective inverse diffusion for signal enhancement in the presence of noise. - Guy Gilboa; Yehoshua Y. Zeevi; Nir A. Sochen (ICASSP, 2000)

Image enhancement segmentation and denoising by time dependent nonlinear diffusion processes. - Guy Gilboa; Yehoshua Y. Zeevi; Nir A. Sochen (ICIP (3), 2001)

Complex Diffusion Processes for Image Filtering. - Guy Gilboa; Yehoshua Y. Zeevi; Nir A. Sochen (Scale-Space, 2001)

Regularized Shock Filters and Complex Diffusion. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (ECCV (1), 2002)

Forward-and-backward diffusion processes for adaptive image enhancement and denoising. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (IEEE Trans. Image Process., 2002)

PDE-based denoising of complex scenes using a spatially-varying fidelity term. - Guy Gilboa; Yehoshua Y. Zeevi; Nir A. Sochen (ICIP (1), 2003)

Image Sharpening by Flows Based on Triple Well Potentials. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (J. Math. Imaging Vis., 2004)

Image Enhancement and Denoising by Complex Diffusion Processes. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (IEEE Trans. Pattern Anal. Mach. Intell., 2004)

Estimation of the Optimal Variational Parameter via SNR Analysis. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (Scale-Space, 2005)

Structure-Texture Decomposition by a TV-Gabor Model. - Jean-François Aujol; Guy Gilboa; Tony F. Chan; Stanley J. Osher (VLSM, 2005)

Nonlinear Inverse Scale Space Methods for Image Restoration. - Martin Burger 001; Stanley J. Osher; Jinjun Xu; Guy Gilboa (VLSM, 2005)

Structure-Texture Image Decomposition - Modeling, Algorithms, and Parameter Selection. - Jean-François Aujol; Guy Gilboa; Tony F. Chan; Stanley J. Osher (Int. J. Comput. Vis., 2006)

Constrained and SNR-Based Solutions for TV-Hilbert Space Image Denoising. - Jean-François Aujol; Guy Gilboa (J. Math. Imaging Vis., 2006)

Estimation of optimal PDE-based denoising in the SNR sense. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (IEEE Trans. Image Process., 2006)

Variational denoising of partly textured images by spatially varying constraints. - Guy Gilboa; Nir A. Sochen; Yehoshua Y. Zeevi (IEEE Trans. Image Process., 2006)

Nonlocal evolutions for image regularization. - Guy Gilboa; Stanley J. Osher (Computational Imaging, 2007)

Nonlocal Linear Image Regularization and Supervised Segmentation. - Guy Gilboa; Stanley J. Osher (Multiscale Model. Simul., 2007)

Nonlocal Operators with Applications to Image Processing. - Guy Gilboa; Stanley J. Osher (Multiscale Model. Simul., 2008)

Nonlinear Scale Space with Spatially Varying Stopping Time. - Guy Gilboa (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Theoretical Foundations for Discrete Forward-and-Backward Diffusion Filtering. - Martin Welk; Guy Gilboa; Joachim Weickert (SSVM, 2009)

Expert Regularizers for Task Specific Processing. - Guy Gilboa (SSVM, 2013)

A Spectral Approach to Total Variation. - Guy Gilboa (SSVM, 2013)

Nonlinear band-pass filtering using the TV transform. - Guy Gilboa (EUSIPCO, 2014)

A Total Variation Spectral Framework for Scale and Texture Analysis. - Guy Gilboa (SIAM J. Imaging Sci., 2014)

Learning Nonlinear Spectral Filters for Color Image Reconstruction. - Michael Möller 001; Julia Diebold; Guy Gilboa; Daniel Cremers (ICCV, 2015)

On the role of non-local Menger curvature in image processing. - Guy Gilboa; Eli Appleboim; Emil Saucan; Yehoshua Y. Zeevi (ICIP, 2015)

A maximal interest-point strategy applied to image enhancement with external priors. - Oren Katzir; Guy Gilboa (ICIP, 2015)

Fundamentals of Non-Local Total Variation Spectral Theory. - Jean-François Aujol; Guy Gilboa; Nicolas Papadakis (SSVM, 2015)

Spectral Representations of One-Homogeneous Functionals. - Martin Burger 001; Lina Eckardt; Guy Gilboa; Michael Möller 001 (SSVM, 2015)

Multiscale Texture Orientation Analysis Using Spectral Total-Variation Decomposition. - Dikla Horesh; Guy Gilboa (SSVM, 2015)

Robust Recovery of Heavily Degraded Depth Measurements. - Gilad Drozdov; Yevgengy Shapiro; Guy Gilboa (3DV, 2016)

A Depth Restoration Occlusionless Temporal Dataset. - Daniel Rotman; Guy Gilboa (3DV, 2016)

Automatic coronary lumen segmentation with partial volume modeling improves lesions' hemodynamic significance assessment. - Moti Freiman; Yechiel Lamash; Guy Gilboa; Hannes Nickisch; Sven Prevrhal; Holger Schmitt; Mani Vembar; Liran Goshen (Image Processing, 2016)

Nonlinear Spectral Analysis via One-Homogeneous Functionals: Overview and Future Prospects. - Guy Gilboa; Michael Möller 001; Martin Burger 001 (J. Math. Imaging Vis., 2016)

Spectral Decompositions Using One-Homogeneous Functionals. - Martin Burger 001; Guy Gilboa; Michael Möller 001; Lina Eckardt; Daniel Cremers (SIAM J. Imaging Sci., 2016)

Separation Surfaces in the Spectral TV Domain for Texture Decomposition. - Dikla Horesh; Guy Gilboa (IEEE Trans. Image Process., 2016)

In situ target-less calibration of turbid media. - Ori Spier; Tali Treibitz; Guy Gilboa (ICCP, 2017)

Nonlinear Spectral Image Fusion. - Martin Benning; Michael Möller 001; Raz Z. Nossek; Martin Burger 001; Daniel Cremers; Guy Gilboa; Carola-Bibiane Schönlieb (SSVM, 2017)

Learning Filter Functions in Regularisers by Minimising Quotients. - Martin Benning; Guy Gilboa; Joana Sarah Grah; Carola-Bibiane Schönlieb (SSVM, 2017)

Semi-Inner-Products for Convex Functionals and Their Use in Image Decomposition. - Guy Gilboa (J. Math. Imaging Vis., 2017)

Blind Facial Image Quality Enhancement Using Non-Rigid Semantic Patches. - Ester Hait; Guy Gilboa (IEEE Trans. Image Process., 2017)

Energy dissipating flows for solving nonlinear eigenpair problems. - Ido Cohen 001; Guy Gilboa (J. Comput. Phys., 2018)

A Discrete Theory and Efficient Algorithms for Forward-and-Backward Diffusion Filtering. - Martin Welk; Joachim Weickert; Guy Gilboa (J. Math. Imaging Vis., 2018)

Flows Generating Nonlinear Eigenfunctions. - Raz Z. Nossek; Guy Gilboa (J. Sci. Comput., 2018)

Theoretical Analysis of Flows Estimating Eigenfunctions of One-Homogeneous Functionals. - Jean-François Aujol; Guy Gilboa; Nicolas Papadakis (SIAM J. Imaging Sci., 2018)

Nonlinear Eigenproblems in Image Processing and Computer Vision - Guy Gilboa (Springer, 2018)

Stable Explicit p-Laplacian Flows Based on Nonlinear Eigenvalue Analysis. - Ido Cohen 001; Adi Falik; Guy Gilboa (SSVM, 2019)

Image-Guided Depth Sampling and Reconstruction. - Adam Wolff; Shachar Praisler; Ilya Tcenov; Guy Gilboa (CoRR, 2019)

Numeric Solutions of Eigenvalue Problems for Generic Nonlinear Operators. - Ester Hait-Fraenkel; Guy Gilboa (CoRR, 2019)

Self-Supervised Unconstrained Illumination Invariant Representation. - Damian Kaliroff; Guy Gilboa (CoRR, 2019)

Spectral Total-Variation Local Scale Signatures for Image Manipulation and Fusion. - Ester Hait; Guy Gilboa (IEEE Trans. Image Process., 2019)

Super-Pixel Sampler: a Data-driven Approach for Depth Sampling and Reconstruction. - Adam Wolff; Shachar Praisler; Ilya Tcenov; Guy Gilboa (ICRA, 2020)

Deeply Learned Spectral Total Variation Decomposition. - Tamara G. Grossmann; Yury Korolev; Guy Gilboa; Carola B. Schönlieb (NeurIPS, 2020)

Unsupervised Enhancement of Real-World Depth Images Using Tri-Cycle GAN. - Alona Baruhov; Guy Gilboa (CoRR, 2020)

Mode Decomposition for Homogeneous Symmetric Operators. - Ido Cohen 001; Omri Azencot; Pavel Lifshitz; Guy Gilboa (CoRR, 2020)

Iterative Methods for Computing Eigenvectors of Nonlinear Operators. - Guy Gilboa (CoRR, 2020)

Experts with Lower-Bounded Loss Feedback: A Unifying Framework. - Eyal Gofer; Guy Gilboa (CoRR, 2020)

Introducing the p-Laplacian spectra. - Ido Cohen 001; Guy Gilboa (Signal Process., 2020)

PhIT-Net: Photo-consistent Image Transform for Robust Illumination Invariant Matching. - Damian Kaliroff; Guy Gilboa (BMVC, 2021)

Nonlinear Spectral Processing of Shapes via Zero-Homogeneous Flows. - Jonathan Brokman; Guy Gilboa (SSVM, 2021)

Total-Variation Mode Decomposition. - Ido Cohen 001; Tom Berkov; Guy Gilboa (SSVM, 2021)

A Pseudo-Inverse for Nonlinear Operators. - Eyal Gofer; Guy Gilboa (CoRR, 2021)

Revealing stable and unstable modes of denoisers through nonlinear eigenvalue analysis. - Ester Hait-Fraenkel; Guy Gilboa (J. Vis. Commun. Image Represent., 2021)

Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks. - Leon Bungert; Ester Hait-Fraenkel; Nicolas Papadakis; Guy Gilboa (SIAM J. Imaging Sci., 2021)

Modes of Homogeneous Gradient Flows. - Ido Cohen 001; Omri Azencot; Pavel Lifshits; Guy Gilboa (SIAM J. Imaging Sci., 2021)

Adaptive LiDAR Sampling and Depth Completion Using Ensemble Variance. - Eyal Gofer; Shachar Praisler; Guy Gilboa (IEEE Trans. Image Process., 2021)

How to Guide Adaptive Depth Sampling? - Ilya Tcenov; Guy Gilboa (CoRR, 2022)

Analysis of Branch Specialization and its Application in Image Decomposition. - Jonathan Brokman; Guy Gilboa (CoRR, 2022)

The Underlying Correlated Dynamics in Neural Training. - Rotem Turjeman; Tom Berkov; Ido Cohen 001; Guy Gilboa (CoRR, 2022)

Adaptive Anisotropic Total Variation: Analysis and Experimental Findings of Nonlinear Spectral Properties. - Shai Biton; Guy Gilboa (J. Math. Imaging Vis., 2022)

BASiS: Batch Aligned Spectral Embedding Space. - Or Streicher; Ido Cohen 001; Guy Gilboa (CVPR, 2023)

EPiC: Ensemble of Partial Point Clouds for Robust Classification. - Meir Yossef Levi; Guy Gilboa (ICCV, 2023)

Theoretical Foundations for Pseudo-Inversion of Nonlinear Operators. - Eyal Gofer; Guy Gilboa (SSVM, 2023)

Graph Laplacian for Semi-supervised Learning. - Or Streicher; Guy Gilboa (SSVM, 2023)

Additive Class Distinction Maps using Branched-GANs. - Elnatan Kadar; Jonathan Brokman; Guy Gilboa (CoRR, 2023)

Minimizing Quotient Regularization Model. - Chao Wang 067; Jean-François Aujol; Guy Gilboa; Yifei Lou (CoRR, 2023)

Critical Points ++: An Agile Point Cloud Importance Measure for Robust Classification, Adversarial Defense and Explainable AI. - Meir Yossef Levi; Guy Gilboa (CoRR, 2023)

Enhancing Neural Training via a Correlated Dynamics Model. - Jonathan Brokman; Roy Betser; Rotem Turjeman; Tom Berkov; Ido Cohen 001; Guy Gilboa (ICLR, 2024)

DXAI: Explaining Classification by Image Decomposition. - Elnatan Kadar; Guy Gilboa (CoRR, 2024)

Fast and Simple Explainability for Point Cloud Networks. - Meir Yossef Levi; Guy Gilboa (CoRR, 2024)

The Double-Ellipsoid Geometry of CLIP. - Meir Yossef Levi; Guy Gilboa (CoRR, 2024)

Spectral Total-variation Processing of Shapes - Theory and Applications. - Jonathan Brokman; Martin Burger 001; Guy Gilboa (ACM Trans. Graph., 2024)

Generalized Inversion of Nonlinear Operators. - Eyal Gofer; Guy Gilboa (J. Math. Imaging Vis., 2024)

Robustifying Point Cloud Networks by Refocusing. - Meir Yossef Levi; Guy Gilboa (3DV, 2025)

Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images. - Jonathan Brokman; Amit Giloni; Omer Hofman; Roman Vainshtein; Hisashi Kojima; Guy Gilboa (ICLR, 2025)

Identifying Memorization of Diffusion Models Through p-Laplace Analysis. - Jonathan Brokman; Amit Giloni; Omer Hofman; Roman Vainshtein; Hisashi Kojima; Guy Gilboa (SSVM (1), 2025)

Whitened CLIP as a Likelihood Surrogate of Images and Captions. - Roy Betser; Meir Yossef Levi; Guy Gilboa (CoRR, 2025)

Ensemble of Weak Spectral Total Variation Learners: a PET-CT Case Study. - Anna Rosenberg; John A. Kennedy; Zohar Keidar; Yehoshua Y. Zeevi; Guy Gilboa (CoRR, 2025)