A Variational Approach for Object Contour Tracking. - Nicolas Papadakis; Étienne Mémin; Frédéric Cao (VLSM, 2005)

Dense Estimation of Layer Motions in the Atmosphere. - Patrick Héas; Étienne Mémin; Nicolas Papadakis (ICPR (3), 2006)

Image Assimilation for Motion Estimation of Atmospheric Layers with Shallow-Water Model. - Nicolas Papadakis; Patrick Héas; Étienne Mémin (ACCV (1), 2007)

Dynamically consistent optical flow estimation. - Nicolas Papadakis; Thomas Corpetti; Étienne Mémin (ICCV, 2007)

Variational optimal control technique for the tracking of deformable objects. - Nicolas Papadakis; Étienne Mémin (ICCV, 2007)

Dense estimation of motion fields on meteosat second generation images using a dynamical consistency. - Thomas Corpetti; Nicolas Papadakis; Étienne Mémin (IGARSS, 2007)

A Consistent Spatio-temporal Motion Estimator for Atmospheric Layers. - Patrick Héas; Étienne Mémin; Nicolas Papadakis (SSVM, 2007)

A Variational Framework for Spatio-temporal Smoothing of Fluid Motions. - Nicolas Papadakis; Étienne Mémin (SSVM, 2007)

Layered Estimation of Atmospheric Mesoscale Dynamics From Satellite Imagery. - Patrick Héas; Étienne Mémin; Nicolas Papadakis; André Szantai (IEEE Trans. Geosci. Remote. Sens., 2007)

Assimilation de données images : application au suivi de courbes et de champs de vecteurs. - Nicolas Papadakis (2007)

Variational Pressure Image Assimilation for Atmospheric Motion Estimation. - Thomas Corpetti; Patrick Héas; Étienne Mémin; Nicolas Papadakis (IGARSS (2), 2008)

A Variational Technique for Time Consistent Tracking of Curves and Motion. - Nicolas Papadakis; Étienne Mémin (J. Math. Imaging Vis., 2008)

Variational Assimilation of Fluid Motion from Image Sequence. - Nicolas Papadakis; Étienne Mémin (SIAM J. Imaging Sci., 2008)

Polyconvexification of the multi-label optical flow problem. - Nicolas Papadakis; Antonio Baeza; Pau Gargallo; Vicent Caselles (ICIP, 2010)

Stereoscopic Image Inpainting: Distinct Depth Maps and Images Inpainting. - Alexandre Hervieu; Nicolas Papadakis; Aurélie Bugeau; Pau Gargallo; Vicent Caselles (ICPR, 2010)

Coherent Background Video Inpainting through Kalman Smoothing along Trajectories. - Aurélie Bugeau; Pau Gargallo; Olivier D'Hondt; Alexandre Hervieu; Nicolas Papadakis; Vicent Caselles (VMV, 2010)

Multi-label Depth Estimation for Graph Cuts Stereo Problems. - Nicolas Papadakis; Vicent Caselles (J. Math. Imaging Vis., 2010)

A Narrow Band Method for the Convex Formulation of Discrete Multilabel Problems. - Antonio Baeza; Vicent Caselles; Pau Gargallo; Nicolas Papadakis (Multiscale Model. Simul., 2010)

Stereoscopic image inpainting using scene geometry. - Alexandre Hervieu; Nicolas Papadakis; Aurélie Bugeau; Pau Gargallo; Vicent Caselles (ICME, 2011)

Tracking with Occlusions via Graph Cuts. - Nicolas Papadakis; Aurélie Bugeau (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

A Variational Model for Histogram Transfer of Color Images. - Nicolas Papadakis; Edoardo Provenzi; Vicent Caselles (IEEE Trans. Image Process., 2011)

Active contours without level sets. - Romain Yildizoglu; Jean-François Aujol; Nicolas Papadakis (ICIP, 2012)

Virtual camera synthesis for soccer game replays. - Nicolas Papadakis; Antonio Baeza; Aurélie Bugeau; Pau Gargallo; Olivier D'Hondt; Vicent Caselles; Xavier Armangué; Ignasi Rius; Sergi Sagàs (J. Virtual Real. Broadcast., 2012)

A Convex Formulation for Global Histogram Based Binary Segmentation. - Romain Yildizoglu; Jean-François Aujol; Nicolas Papadakis (EMMCVPR, 2013)

Regularized Discrete Optimal Transport. - Sira Ferradans; Nicolas Papadakis; Julien Rabin; Gabriel Peyré; Jean-François Aujol (SSVM, 2013)

High-Dimension Multilabel Problems: Convex or Nonconvex Relaxation? - Nicolas Papadakis; Romain Yildizoglu; Jean-François Aujol; Vicent Caselles (SIAM J. Imaging Sci., 2013)

Exemplar-based colorization in RGB color space. - Fabien Pierre; Jean-François Aujol; Aurélie Bugeau; Nicolas Papadakis; Vinh-Thong Ta 002 (ICIP, 2014)

Adaptive color transfer with relaxed optimal transport. - Julien Rabin; Sira Ferradans; Nicolas Papadakis (ICIP, 2014)

Regularized Discrete Optimal Transport. - Sira Ferradans; Nicolas Papadakis; Gabriel Peyré; Jean-François Aujol (SIAM J. Imaging Sci., 2014)

Optimal Transport with Proximal Splitting. - Nicolas Papadakis; Gabriel Peyré; Édouard Oudet (SIAM J. Imaging Sci., 2014)

Variational Exemplar-Based Image Colorization. - Aurélie Bugeau; Vinh-Thong Ta 002; Nicolas Papadakis (IEEE Trans. Image Process., 2014)

Optimal Transport for Image Processing. (Transport Optimal pour le Traitement d'Images). - Nicolas Papadakis (2015)

Non-convex Relaxation of Optimal Transport for Color Transfer Between Images. - Julien Rabin; Nicolas Papadakis (GSI, 2015)

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

On Debiasing Restoration Algorithms: Applications to Total-Variation and Nonlocal-Means. - Charles-Alban Deledalle; Nicolas Papadakis; Joseph Salmon (SSVM, 2015)

Convex Color Image Segmentation with Optimal Transport Distances. - Julien Rabin; Nicolas Papadakis (SSVM, 2015)

Luminance-Chrominance Model for Image Colorization. - Fabien Pierre; Jean-François Aujol; Aurélie Bugeau; Nicolas Papadakis; Vinh-Thong Ta 002 (SIAM J. Imaging Sci., 2015)

SCALP: Superpixels with Contour Adherence using Linear Path. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis (ICPR, 2016)

CLEAR: Covariant LEAst-square Re-fitting with applications to image restoration. - Charles-Alban Deledalle; Nicolas Papadakis; Joseph Salmon; Samuel Vaiter (CoRR, 2016)

Guest Editorial: Scale-Space and Variational Methods. - Jean-François Aujol; Mila Nikolova; Nicolas Papadakis (J. Math. Imaging Vis., 2016)

An Optimized PatchMatch for multi-scale and multi-feature label fusion. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis; José V. Manjón; D. Louis Collins; Pierrick Coupé (NeuroImage, 2016)

Luminance-Guided Chrominance Denoising with Debiased Coupled Total Variation. - Fabien Pierre; Jean-François Aujol; Charles-Alban Deledalle; Nicolas Papadakis (EMMCVPR, 2017)

Regularized Barycenters in the Wasserstein Space. - Elsa Cazelles; Jérémie Bigot; Nicolas Papadakis (GSI, 2017)

Superpixel-based color transfer. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis (ICIP, 2017)

Robust shape regularity criteria for superpixel evaluation. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis (ICIP, 2017)

Parameter Estimation in Finite Mixture Models by Regularized Optimal Transport: A Unified Framework for Hard and Soft Clustering. - Arnaud Dessein; Nicolas Papadakis; Charles-Alban Deledalle (CoRR, 2017)

Evaluation framework of superpixel methods with a global regularity measure. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis (J. Electronic Imaging, 2017)

Convex Histogram-Based Joint Image Segmentation with Regularized Optimal Transport Cost. - Nicolas Papadakis; Julien Rabin (J. Math. Imaging Vis., 2017)

CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration. - Charles-Alban Deledalle; Nicolas Papadakis; Joseph Salmon; Samuel Vaiter (SIAM J. Imaging Sci., 2017)

SuperPatchMatch: An Algorithm for Robust Correspondences Using Superpixel Patches. - Rémi Giraud; Vinh-Thong Ta 002; Aurélie Bugeau; Pierrick Coupé; Nicolas Papadakis (IEEE Trans. Image Process., 2017)

Robust superpixels using color and contour features along linear path. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis (Comput. Vis. Image Underst., 2018)

Regularized Optimal Transport and the Rot Mover's Distance. - Arnaud Dessein; Nicolas Papadakis; Jean-Luc Rouas (J. Mach. Learn. Res., 2018)

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

Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space. - Elsa Cazelles; Vivien Seguy; Jérémie Bigot; Marco Cuturi; Nicolas Papadakis (SIAM J. Sci. Comput., 2018)

Texture-Aware Superpixel Segmentation. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis; Yannick Berthoumieu (ICIP, 2019)

Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Nicolas Papadakis; David Coomes; Anita Faul; Carola-Bibiane Schönlieb (IGARSS, 2019)

GraphX $$^ mathbf{ small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (MICCAI (6), 2019)

Refitting Solutions Promoted by ℓ _12 Sparse Analysis Regularizations with Block Penalties. - Charles-Alban Deledalle; Nicolas Papadakis; Joseph Salmon; Samuel Vaiter (SSVM, 2019)

An Optimized PatchMatch for Multi-scale and Multi-feature Label Fusion. - Rémi Giraud; Vinh-Thong Ta 002; Nicolas Papadakis; José V. Manjón; D. Louis Collins; Pierrick Coupé; Alzheimer's Disease Neuroimaging Initiative (CoRR, 2019)

Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Samar M. Alsaleh; Robby T. Tan; Carola-Bibiane Schönlieb (CoRR, 2019)

A multi-task U-net for segmentation with lazy labels. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Peter Schütz; Carola-Bibiane Schönlieb (CoRR, 2019)

GraphXNET-Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (CoRR, 2019)

Penalization of Barycenters in the Wasserstein Space. - Jérémie Bigot; Elsa Cazelles; Nicolas Papadakis (SIAM J. Math. Anal., 2019)

Learning to Segment Microscopy Images with Lazy Labels. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Peter Schütz; Carola-Bibiane Schönlieb (ECCV Workshops (1), 2020)

Development of an Image De-Noising Method in Preparation for the Surface Water and Ocean Topography Satellite Mission. - Laura Gómez-Navarro; Emmanuel Cosme; Julien Le Sommer; Nicolas Papadakis; Ananda Pascual (Remote. Sens., 2020)

Variational Osmosis for Non-Linear Image Fusion. - Simone Parisotto; Luca Calatroni; Aurélie Bugeau; Nicolas Papadakis; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2020)

Where Are My Clothes? A Multi-Level Approach for Evaluating Deep Instance Segmentation Architectures on Fashion Images. - Warren Jouanneau; Aurélie Bugeau; Marc Palyart; Nicolas Papadakis; Laurent Vézard (CVPR Workshops, 2021)

POPCORN: Progressive Pseudo-Labeling with Consistency Regularization and Neighboring. - Reda Abdellah Kamraoui; Vinh-Thong Ta 002; Nicolas Papadakis; Fanny Compaire; José V. Manjón; Pierrick Coupé (MICCAI (2), 2021)

Wasserstein Generative Models for Patch-Based Texture Synthesis. - Antoine Houdard; Arthur Leclaire; Nicolas Papadakis; Julien Rabin (SSVM, 2021)

Learning Local Regularization for Variational Image Restoration. - Jean Prost; Antoine Houdard; Andrés Almansa; Nicolas Papadakis (SSVM, 2021)

Overrelaxed Sinkhorn-Knopp Algorithm for Regularized Optimal Transport. - Alexis Thibault; Lénaïc Chizat; Charles Dossal; Nicolas Papadakis (Algorithms, 2021)

On the Existence of Optimal Transport Gradient for Learning Generative Models. - Antoine Houdard; Arthur Leclaire; Nicolas Papadakis; Julien Rabin (CoRR, 2021)

Block-Based Refitting in ℓ 12 Sparse Regularization. - Charles-Alban Deledalle; Nicolas Papadakis; Joseph Salmon; Samuel Vaiter (J. Math. Imaging Vis., 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)

Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Mark Kirkland; Peter Schütz; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2021)

Gradient Step Denoiser for convergent Plug-and-Play. - Samuel Hurault; Arthur Leclaire; Nicolas Papadakis (ICLR, 2022)

Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization. - Samuel Hurault; Arthur Leclaire; Nicolas Papadakis (ICML, 2022)

Multi-modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification. - Angelica I. Avilés-Rivero; Christina Runkel; Nicolas Papadakis; Zoe Kourtzi; Carola-Bibiane Schönlieb (MICCAI (3), 2022)

Diverse super-resolution with pretrained deep hiererarchical VAEs. - Jean Prost; Antoine Houdard; Nicolas Papadakis; Andrés Almansa (CoRR, 2022)

A patch-based architecture for multi-label classification from single label annotations. - Warren Jouanneau; Aurélie Bugeau; Marc Palyart; Nicolas Papadakis; Laurent Vézard (CoRR, 2022)

GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays. - Angelica I. Avilés-Rivero; Philip Sellars; Carola-Bibiane Schönlieb; Nicolas Papadakis (Pattern Recognit., 2022)

SCOTCH and SODA: A Transformer Video Shadow Detection Framework. - Lihao Liu; Jean Prost; Lei Zhu 003; Nicolas Papadakis; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CVPR, 2023)

Inverse problem regularization with hierarchical variational autoencoders. - Jean Prost; Antoine Houdard; Andrés Almansa; Nicolas Papadakis (ICCV, 2023)

Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems. - Samuel Hurault; Ulugbek Kamilov; Arthur Leclaire; Nicolas Papadakis (NeurIPS, 2023)

A Relaxed Proximal Gradient Descent Algorithm for Convergent Plug-and-Play with Proximal Denoiser. - Samuel Hurault; Antonin Chambolle; Arthur Leclaire; Nicolas Papadakis (SSVM, 2023)

A Patch-Based Architecture for Multi-Label Classification from Single Positive Annotations. - Warren Jouanneau; Aurélie Bugeau; Marc Palyart; Nicolas Papadakis; Laurent Vézard (VISIGRAPP (5: VISAPP), 2023)

Single-Image based unsupervised joint segmentation and denoising. - Nadja Gruber; Johannes Schwab; Noémie Debroux; Nicolas Papadakis; Markus Haltmeier (CoRR, 2023)

On the Gradient Formula for learning Generative Models with Regularized Optimal Transport Costs. - Antoine Houdard; Arthur Leclaire; Nicolas Papadakis; Julien Rabin (Trans. Mach. Learn. Res., 2023)

A Generative Model for Texture Synthesis based on Optimal Transport Between Feature Distributions. - Antoine Houdard; Arthur Leclaire; Nicolas Papadakis; Julien Rabin (J. Math. Imaging Vis., 2023)

A Unified Framework for Hard and Soft Clustering with Regularized Optimal Transport. - Jean-Frédéric Diebold; Nicolas Papadakis; Arnaud Dessein; Charles-Alban Deledalle (EUSIPCO, 2024)

Plug-and-Play image restoration with Stochastic deNOising REgularization. - Marien Renaud; Jean Prost; Arthur Leclaire; Nicolas Papadakis (ICML, 2024)

Efficient Posterior Sampling for Diverse Super-Resolution with Hierarchical VAE Prior. - Jean Prost; Antoine Houdard; Andrés Almansa; Nicolas Papadakis (VISIGRAPP (3): VISAPP, 2024)

Non-local Matching of Superpixel-based Deep Features for Color Transfer and Colorization. - Roxane Leduc; Hernan Carrillo; Nicolas Papadakis (Image Process. Line, 2024)

Convergent Plug-and-Play with Proximal Denoiser and Unconstrained Regularization Parameter. - Samuel Hurault; Antonin Chambolle; Arthur Leclaire; Nicolas Papadakis (J. Math. Imaging Vis., 2024)

Convergence Analysis of a Proximal Stochastic Denoising Regularization Algorithm. - Marien Renaud; Julien Hermant; Nicolas Papadakis (SSVM (2), 2025)

Equivariant Denoisers for Image Restoration. - Marien Renaud; Arthur Leclaire; Nicolas Papadakis (SSVM (1), 2025)

LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization. - Alessio Spagnoletti; Jean Prost; Andrés Almansa; Nicolas Papadakis; Marcelo Pereyra (CoRR, 2025)

From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling. - Marien Renaud; Valentin De Bortoli; Arthur Leclaire; Nicolas Papadakis (CoRR, 2025)