Aujol, J.
* 2013: High-Dimension Multilabel Problems: Convex or Nonconvex Relaxation?
* 2019: LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net
Aujol, J.F.[Jean Francois]
* 2002: Signed distance functions and viscosity solutions of discontinuous Hamilton-Jacobi Equations
* 2002: Supervised classification for textured images
* 2003: Image Decomposition Application to SAR Images
* 2003: Image decomposition: application to textured images and SAR images
* 2003: Modeling very oscillating signals. Application to image processing
* 2003: Wavelet-based level set evolution for classification of textured images
* 2003: Wavelet-based level set evolution for classification of textured images
* 2005: Detecting Codimension: Two Objects in an Image with Ginzburg-Landau Models
* 2005: Dual Norms and Image Decomposition Models
* 2005: Image Decomposition into a Bounded Variation Component and an Oscillating Component
* 2006: Color image decomposition and restoration
* 2006: Combining geometrical and textured information to perform image classification
* 2006: Constrained and SNR-Based Solutions for TV-Hilbert Space Image Denoising
* 2006: Structure-Texture Image Decomposition: Modeling, Algorithms, and Parameter Selection
* 2007: Nonconvex Model to Remove Multiplicative Noise, A
* 2007: Resolution-Independent Characteristic Scale Dedicated to Satellite Images
* 2008: Indexing of Satellite Images With Different Resolutions by Wavelet Features
* 2009: Integrating the Normal Field of a Surface in the Presence of Discontinuities
* 2009: Local Scale Measure for Remote Sensing Images
* 2009: Locally Parallel Textures Modeling with Adapted Hilbert Spaces
* 2009: Projected Gradient Based Color Image Decomposition
* 2009: Some First-Order Algorithms for Total Variation Based Image Restoration
* 2010: Mathematical Modeling of Textures: Application to Color Image Decomposition with a Projected Gradient Algorithm
* 2011: Bias-Variance Approach for the Nonlocal Means, A
* 2011: Locally Parallel Texture Modeling
* 2011: On the efficiency of proximal methods in CBCT and PET
* 2012: Active contours without level sets
* 2012: Compact representations of stationary dynamic textures
* 2013: Regularized Discrete Optimal Transport
* 2013: Static and Dynamic Texture Mixing Using Optimal Transport
* 2014: Adaptive regularization of the NL-means for video denoising
* 2014: Adaptive Regularization of the NL-Means: Application to Image and Video Denoising
* 2014: Exemplar-based colorization in RGB color space
* 2014: Poisson Skeleton Revisited: a New Mathematical Perspective
* 2014: Regularized Discrete Optimal Transport
* 2014: Super-resolution from a low- and partial high-resolution image pair
* 2014: Synthesizing and Mixing Stationary Gaussian Texture Models
* 2014: Unified Model for Image Colorization, A
* 2015: Edge-Based Multi-modal Registration and Application for Night Vision Devices
* 2015: Estimation of the Noise Level Function Based on a Nonparametric Detection of Homogeneous Image Regions
* 2015: Fundamentals of Non-Local Total Variation Spectral Theory
* 2015: Luminance-Chrominance Model for Image Colorization
* 2015: Luminance-Hue Specification in the RGB Space
* 2016: Guest Editorial: Scale-Space and Variational Methods
* 2016: Image Zoom Completion
* 2016: Texture synthesis guided by a low-resolution image
* 2016: Visibility estimation and joint inpainting of lidar depth maps
* 2017: Interactive Video Colorization Within a Variational Framework
* 2017: Joint inpainting of depth and reflectance with visibility estimation
* 2017: Luminance-Guided Chrominance Denoising with Debiased Coupled Total Variation
* 2017: Texture Reconstruction Guided by a High-Resolution Patch
* 2017: Variational Contrast Enhancement of Gray-Scale and RGB Images
* 2018: Normal Integration: A Survey
* 2018: Theoretical Analysis of Flows Estimating Eigenfunctions of One-Homogeneous Functionals
* 2018: Variational Methods for Normal Integration
* 2019: Alternate Structural-Textural Video Inpainting for Spot Defects Correction in Movies
* 2019: Diffusion and inpainting of reflectance and height LiDAR orthoimages
* 2019: Guest Editorial JMIV Special Issue Mathematics and Image Analysis (MIA)
* 2020: Projected Gradient Descent for Non-Convex Sparse Spike Estimation
* 2020: Residual Dense Generative Adversarial Network For Pansharpening With Geometrical Constraints, A
* 2021: Learning Defects in Old Movies from Manually Assisted Restoration
* 2021: Sketched Learning for Image Denoising
* 2022: Compressive Learning for Patch-Based Image Denoising
* 2022: Generative Adversarial Network for Pansharpening With Spectral and Spatial Discriminators
* 2023: Compressive Learning of Deep Regularization for Denoising
Includes: Aujol, J.F.[Jean Francois] Aujol, J.F.[Jean-Francois] Aujol, J.F.[Jean-François] Aujol, J.F. Aujol, J.F.[Jean-Franois] Aujol, J.F.[Jean-Franois]
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