61 citations · 97 across the 23 of their papers we have counts for
15 papers · 1 filter
Teach me to segment with mixed supervision: Confident students become masters
Jose Dolz, Christian Desrosiers, Ismail Ben Ayed
Deep segmentation neural networks require large training datasets with pixel-wise segmentations, which are expensive to obtain in practice. Mixed supervision could mitigate this di…
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Malik Boudiaf, Hoel Kervadec, Ziko Imtiaz Masud +3
We show that the way inference is performed in few-shot segmentation tasks has a substantial effect on performances -- an aspect often overlooked in the literature in favor of the…
Deep Active Learning for Joint Classification & Segmentation with Weak Annotator
Soufiane Belharbi, Ismail Ben Ayed, Luke McCaffrey +1
CNN visualization and interpretation methods, like class-activation maps (CAMs), are typically used to highlight the image regions linked to class predictions. These models allow t…
Augmented Lagrangian Adversarial Attacks
Jérôme Rony, Eric Granger, Marco Pedersoli +1
Adversarial attack algorithms are dominated by penalty methods, which are slow in practice, or more efficient distance-customized methods, which are heavily tailored to the propert…
Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty
Soufiane Belharbi, Jérôme Rony, Jose Dolz +3
Weakly-supervised learning (WSL) has recently triggered substantial interest as it mitigates the lack of pixel-wise annotations. Given global image labels, WSL methods yield pixel-…
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
Adrian Galdran, José Dolz, Hadi Chakor +2
Assessing the degree of disease severity in biomedical images is a task similar to standard classification but constrained by an underlying structure in the label space. Such a str…