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20112021
most citedLatent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities

221 citations · 345 across the 15 of their papers we have counts for

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cs.CV20217 cited

Improving Unsupervised Domain Adaptive Re-Identification via Source-Guided Selection of Pseudo-Labeling Hyperparameters

Fabian Dubourvieux, Angélique Loesch, Romaric Audigier +2

Unsupervised Domain Adaptation (UDA) for re-identification (re-ID) is a challenging task: to avoid a costly annotation of additional data, it aims at transferring knowledge from a…

cs.CV20211 cited

A Tri-attention Fusion Guided Multi-modal Segmentation Network

Tongxue Zhou, Su Ruan, Pierre Vera +1

In the field of multimodal segmentation, the correlation between different modalities can be considered for improving the segmentation results. Considering the correlation between…

cs.CV2020

Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling

Fabian Dubourvieux, Romaric Audigier, Angelique Loesch +2

Person Re-Identification (re-ID) aims at retrieving images of the same person taken by different cameras. A challenge for re-ID is the performance preservation when a model is used…

cs.CV2019

Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning

Rachel Blin, Samia Ainouz, Stéphane Canu +1

Object detection in road scenes is necessary to develop both autonomous vehicles and driving assistance systems. Even if deep neural networks for recognition task have shown great…

cs.CV2017

A First Derivative Potts Model for Segmentation and Denoising Using ILP

Ruobing Shen, Gerhard Reinelt, Stéphane Canu

Unsupervised image segmentation and denoising are two fundamental tasks in image processing. Usually, graph based models such as multicut are used for segmentation and variational…