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04/09/2023
On the dice loss gradient and the ways to mimic it
In the past few years, in the context of fully-supervised semantic segme...
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08/06/2021
Source-Free Domain Adaptation for Image Segmentation
Domain adaptation (DA) has drawn high interest for its capacity to adapt...
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05/03/2021
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!
Standard losses for training deep segmentation networks could be seen as...
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12/11/2020
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Few-shot segmentation has recently attracted substantial interest, with ...
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05/07/2020
Source-Relaxed Domain Adaptation for Image Segmentation
Domain adaptation (DA) has drawn high interests for its capacity to adap...
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08/15/2019
Discretely-constrained deep network for weakly supervised segmentation
An efficient strategy for weakly-supervised segmentation is to impose co...
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08/08/2019
Constrained domain adaptation for segmentation
We propose to adapt segmentation networks with a constrained formulation...
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04/10/2019
Curriculum semi-supervised segmentation
This study investigates a curriculum-style strategy for semi-supervised ...
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04/08/2019
Log-barrier constrained CNNs
This study investigates imposing inequality constraints on the outputs o...
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12/17/2018
Boundary loss for highly unbalanced segmentation
Widely used loss functions for convolutional neural network (CNN) segmen...
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05/12/2018
