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09/19/2023
Single-Image based unsupervised joint segmentation and denoising
In this work, we develop an unsupervised method for the joint segmentati...
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06/06/2023
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
Plug-and-Play (PnP) methods are efficient iterative algorithms for solvi...
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03/20/2023
Inverse problem regularization with hierarchical variational autoencoders
In this paper, we propose to regularize ill-posed inverse problems using...
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01/31/2023
A relaxed proximal gradient descent algorithm for convergent plug-and-play with proximal denoiser
This paper presents a new convergent Plug-and-Play (PnP) algorithm. PnP ...
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11/13/2022
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Shadows in videos are difficult to detect because of the large shadow de...
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09/14/2022
A patch-based architecture for multi-label classification from single label annotations
In this paper, we propose a patch-based architecture for multi-label cla...
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05/20/2022
Diverse super-resolution with pretrained deep hiererarchical VAEs
Image super-resolution is a one-to-many problem, but most deep-learning ...
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04/04/2022
Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
The automatic early diagnosis of prodromal stages of Alzheimer's disease...
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01/31/2022
Proximal denoiser for convergent plug-and-play optimization with nonconvex regularization
Plug-and-Play (PnP) methods solve ill-posed inverse problems through ite...
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10/07/2021
Gradient Step Denoiser for convergent Plug-and-Play
Plug-and-Play methods constitute a class of iterative algorithms for ima...
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09/13/2021
POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring
Semi-supervised learning (SSL) uses unlabeled data to compensate for the...
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02/11/2021
Learning local regularization for variational image restoration
In this work, we propose a framework to learn a local regularization mod...
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02/10/2021
On the Existence of Optimal Transport Gradient for Learning Generative Models
The use of optimal transport cost for learning generative models has bec...
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09/30/2020
GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays
Can one learn to diagnose COVID-19 under extreme minimal supervision? Si...
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05/26/2020
Multi-task deep learning for image segmentation using recursive approximation tasks
Fully supervised deep neural networks for segmentation usually require a...
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10/04/2019
Variational Osmosis for Non-linear Image Fusion
We propose a new variational model for nonlinear image fusion. Our appro...
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07/23/2019
GraphX^NET- Chest X-Ray Classification Under Extreme Minimal Supervision
The task of classifying X-ray data is a problem of both theoretical and ...
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06/20/2019
A multi-task U-net for segmentation with lazy labels
The need for labour intensive pixel-wise annotation is a major limitatio...
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06/20/2019
Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian
We consider the task of classifying when an extremely reduced amount of ...
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03/17/2019
Robust superpixels using color and contour features along linear path
Superpixel decomposition methods are widely used in computer vision and ...
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03/17/2019
SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches
Superpixels have become very popular in many computer vision application...
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03/17/2019
An Optimized PatchMatch for Multi-scale and Multi-feature Label Fusion
Automatic segmentation methods are important tools for quantitative anal...
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03/17/2019
Evaluation Framework of Superpixel Methods with a Global Regularity Measure
In the superpixel literature, the comparison of state-of-the-art methods...
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03/17/2019
SCALP: Superpixels with Contour Adherence using Linear Path
Superpixel decomposition methods are generally used as a pre-processing ...
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03/17/2019
Robust Shape Regularity Criteria for Superpixel Evaluation
Regular decompositions are necessary for most superpixel-based object re...
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03/14/2019
Superpixel-based Color Transfer
In this work, we propose a fast superpixel-based color transfer method (...
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01/30/2019
Texture-Aware Superpixel Segmentation
Most superpixel methods are based on spatial and color measures at the p...
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01/27/2019
Approximation of Wasserstein distance with Transshipment
An algorithm for approximating the p-Wasserstein distance between histog...
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04/24/2018
Data-driven regularization of Wasserstein barycenters with an application to multivariate density registration
We present a framework to simultaneously align and smooth data in the fo...
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11/24/2017
Central limit theorems for Sinkhorn divergence between probability distributions on finite spaces and statistical applications
The notion of Sinkhorn divergence has recently gained popularity in mach...
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11/12/2017
Parameter Estimation in Finite Mixture Models by Regularized Optimal Transport: A Unified Framework for Hard and Soft Clustering
In this short paper, we formulate parameter estimation for finite mixtur...
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10/20/2016
Regularized Optimal Transport and the Rot Mover's Distance
This paper presents a unified framework for smooth convex regularization...
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10/05/2016
Convex Histogram-Based Joint Image Segmentation with Regularized Optimal Transport Cost
We investigate in this work a versatile convex framework for multiple im...
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03/06/2015
Convex Color Image Segmentation with Optimal Transport Distances
This work is about the use of regularized optimal-transport distances fo...
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07/21/2013