Jean-François Aujol
- Université de Bordeaux (UB)
- Institut de Mathématiques de Bordeaux (IMB)
Domaines de recherche
Publications
Publications
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Gradient correlation is a key ingredient to accelerate SGD with momentumInternational Conference on Learning Representations, 2025, Apr 2025, Singapour, Singapore |
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Projected Block Coordinate Descent for sparse spike estimation.32nd European Signal Processing Conference (EUSIPCO), Oct 2024, Lyon, France. pp.2667-2671 |
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Compressive learning of deep regularization for denoisingInternational Conference on Scale Space and Variational Methods in Computer Vision (SSVM), May 2023, Cagliari, Italy |
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Découpage automatique de vidéos de sport amateur par détection de personnes et analyse de contenu colorimétriqueORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France |
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Sketched learning for image denoisingThe Eighth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), May 2021, Cabourg, France. pp.281-293, ⟨10.1007/978-3-030-75549-2_23⟩ |
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Détection des défauts dans les vieux films par apprentissage profond à partir d'une restauration semi-manuelleORASIS 2021 - 18èmes journées francophones des jeunes chercheurs en vision par ordinateur, Centre National de la Recherche Scientifique [CNRS]; Equipe REVA, IRIT : Institut de Recherche en Informatique de Toulouse, Sep 2021, Saint Ferréol, France |
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A RESIDUAL DENSE GENERATIVE ADVERSARIAL NETWORK FOR PANSHARPENING WITH GEOMETRICAL CONSTRAINTS27th IEEE international conference on image processing (ICIP 2020), Oct 2020, Abou Dabi, United Arab Emirates |
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An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraintin Proceedings of iTWIST'20, Paper-ID: 7, Nantes, France, December, 2-4, 2020, Dec 2020, Nantes, France |
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Visibility estimation in point clouds with variable densityInternational Conference on Computer Vision Theory and Applications (VISAPP), Feb 2019, Prague, Czech Republic |
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Détection et localisation d'objets 3D par apprentissage profond en topologie capteurGRETSI Groupement de Recherche en Traitement du Signal et de l'Image, Aug 2019, Lille, France |
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Fusion d'images non locale préservant la géométrieGRETSI, Aug 2019, Lille, France |
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LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-NetIEEE International Conference on Computer Vision Workshops (ICCV), Oct 2019, Séoul, South Korea. ⟨10.1109/ICCVW.2019.00123⟩ |
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Alternate Structural-Textural Video Inpainting for Spot Defects Correction in MoviesSSVM 2019 - Seventh International Conference on Scale Space and Variational Methods in Computer Vision, Jun 2019, Hofgeismar, Germany |
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Inpainting vidéo pour la restauration de films par reconstructions alternées de la structure et de la textureORASIS 2019 - 17ème journées francophones des jeunes chercheurs en vision par ordinateur, May 2019, Saint-Dié-des-Vosges, France |
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Estimation de visibilité dans un nuage de points LiDARConférence Annuelle Française de Photogrammétrie et Télédétection (CFPT), Jun 2018, Marne La Vallée, France |
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Disocclusion of 3D LiDAR point clouds using range imagesCity Models, Roads and Traffic workshop (CMRT), Jun 2017, Hannover, Germany. pp.75 - 82, ⟨10.5194/isprs-annals-IV-1-W1-75-2017⟩ |
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Luminance-Guided Chrominance Denoising with Debiased Coupled Total VariationEnergy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'17), Oct 2017, Venise, Italy. pp.235-248 |
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Désoccultation de nuage de points LiDAR en topologie capteurGroupement de Recherche en Traitement du Signal et de l'Image (GRETSI), Sep 2017, Juan-Les-Pins, France |
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Automatic estimation of the noise level function for adaptive blind denoising24th European Signal Processing Conference (EUSIPCO), 2016, Aug 2016, Budapest, Hungary. pp.76 - 80, ⟨10.1109/EUSIPCO.2016.7760213⟩ |
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Diffusion anisotrope et inpainting d'orthophotographies LiDAR mobile20ème Congrès national sur la Reconnaissance des Formes et l'Intelligence Artificielle (RFIA 2016), Jun 2016, Clermont-Ferrand, France |
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Texture synthesis guided by a low-resolution imageWorkshop, IEEE Image Video and Multidimensional Signal Processing (IVMSP), Jul 2016, Bordeaux, France. pp.1 - 5, ⟨10.1109/IVMSPW.2016.7528183⟩ |
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HUE-PRESERVING PERCEPTUAL CONTRAST ENHANCEMENTInternationnal Conference on Image Processing (ICIP), Jun 2016, Phoenix, United States |
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Visibility Estimation and Joint Inpainting of Lidar Depth MapsIEEE International Conference on Image Processing (ICIP), Sep 2016, Phoenix, AZ, United States |
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Luminance-Hue Specification in the RGB SpaceScale-Space and Variational Method in Computer Vision, Jun 2015, Lège Cap-Ferret., France. ⟨10.1007/978-3-319-18461-6_33⟩ |
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Estimation du niveau de bruit par la détection non paramétrique de zones homogènesGretsi, Sep 2015, Lyon, France |
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Combinaison linéaire optimale de métriques pour la colorisation d'imagesGRETSI Groupement de Recherche en Traitement du Signal et de l'Image, Sep 2015, Lyon, France |
Fundamentals of Non-Local Total Variation Spectral TheoryInternational Conference on Scale Space and Variational Methods in Computer Vision (SSVM'15), May 2015, Lège-Cap Ferret, France. pp.66-77, ⟨10.1007/978-3-319-18461-6_6⟩ |
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SUPER-RESOLUTION FROM A LOW- AND PARTIAL HIGH- RESOLUTION IMAGE PAIRInternational Conference on Image Processing, Oct 2014, Paris, France. pp.1 |
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Exemplar-based colorization in RGB color spaceIEEE Internationnal Conference on Image Processing (ICIP'14), Oct 2014, Paris, France. pp.1-5 |
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A Unified Model for Image ColorizationCPCV workshop - European Conference on Computer Vision (ECCV), Sep 2014, Zürich, France. pp.1-12 |
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Adaptive regularization of the NL-means for video denoisingIEEE International Conference on Image Processing 2014, Oct 2014, Paris, France. 5 p |
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A convex formulation for global histogram based binary segmentationEnergy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'13), Aug 2013, Lund, Sweden. pp.1-14 |
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Regularized Discrete Optimal TransportInternational Conference on Scale Space and Variational Methods in Computer Vision (SSVM'13), Jun 2013, Schloss Seggau, Leibnitz, Austria. pp.428-439, ⟨10.1007/978-3-642-38267-3_36⟩ |
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TV-NL : Une coopération entre les NL-means et les méthodes variationnellesGretsi 2013, Sep 2013, Brest, France. 4 p |
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Une formulation convexe pour la segmentation binaire d'images à partir d'histogrammes.Colloque du Groupe de Recherche et d'Etudes de Traitement du Signal et des Images (GRETSI'13), Sep 2013, Brest, France. pp.1-4 |
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Active Contours without Level SetsIEEE International Conference on Image Processing (ICIP'12), Sep 2012, Orlando, Florida, United States. pp.2549-2552, ⟨10.1109/ICIP.2012.6467418⟩ |
Proximal Algorithms and CT: New Results on 3D Real Datas and Color CT2012 SIAM Conference on Imaging Science, Apr 2012, Philadelphie, United States |
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Compact Representations of Stationary Dynamic TexturesICIP'12, Sep 2012, United States |
On the efficiency of proximal methods for CBCT and PETICIP 2011 : 2011 IEEE International Conference on Image Processing, Sep 2011, Bruxelles, Belgium. pp.1365 - 1368, ⟨10.1109/ICIP.2011.6115691⟩ |
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Intégration d’un champ de normales en présence de discontinuitésCongrès Francophone de Reconnaissance des Formes et Intelligence Artificielle (RFIA 2010), AFRIF; AFIA, Jan 2010, Caen, France. (support électronique) |
A comparative review of SAR images speckle denoising methods based on functional minimizationSIAM Conference on Imaging Science, Apr 2010, Chicago, United States |
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Integrating the Normal Field of a Surface in the Presence of Discontinuities7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009), Aug 2009, Bonn, Germany. pp.261--273, ⟨10.1007/978-3-642-03641-5_20⟩ |
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Extraction de textures localement parallèles par un espace de Hilbert adaptéGretsi'09, Sep 2009, Dijon, France |
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Locally Parallel Textures Modeling with Adapted Hilbert SpacesEnergy Minimization Methods in Computer Vision and Pattern Recognition 2009, Aug 2009, Bonn, Germany. pp.429-442, ⟨10.1007/978-3-642-03641-5⟩ |
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Recent Approaches for Image ColorizationHandbook of Mathematical Models and Algorithms in Computer Vision and Imaging, In press, ⟨10.1007/978-3-030-03009-4_55-1⟩ |
Scale Space and Variational Methods in Computer Vision5th International Conference on Scale Space and Variational Methods in Computer Vision, May 2015, Lège Cap Ferret, France. 9087, Springer, 2015, Lecture Notes in Computer Science |
Special issue on Mathematics and Image Analysis in Journal of Mathematical Imaging and Vision48 (2), pp.203-382, 2014 |
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Utilisation de méthodes variationnelles en traitement d'imageMathématiques [math]. École normale supérieure de Cachan - ENS Cachan, 2009 |
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Traitement d'images par approches variationnelles et équations aux dérivées partiellesDEA. 11 avril 2005 au 16 avril 2005 à l'ENIT à Tunis., 2005, pp.55 |
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Structure and texture compressionRR-5076, INRIA. 2004 |
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Detecting codimension-two objects in an image with Ginzburg-Landau modelsRR-5254, INRIA. 2004, pp.28 |
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Dual norms and image decomposition modelsRR-5130, INRIA. 2004 |
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Image decomposition: application to textured images and SAR imagesRR-4704, INRIA. 2003 |
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Modeling very oscillating signals. Application to image processingRR-4878, INRIA. 2003 |
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Supervised classification for textured imagesRR-4640, INRIA. 2002 |
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Signed distance functions and viscosity solutions of discontinuous Hamilton-Jacobi EquationsRR-4507, INRIA. 2002 |
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Contribution à l'analyse de textures en traitement d'images par méthodes variationnelles et équations aux dérivées partiellesMathématiques [math]. Université Nice Sophia Antipolis, 2004. Français. ⟨NNT : ⟩ |