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Few-Shot Semantic Segmentation

4 papers with code · Computer Vision

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Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

25 Apr 2019voxelmorph/voxelmorph

To develop a deep learning-based segmentation model for a new image dataset (e. g., of different contrast), one usually needs to create a new labeled training dataset, which can be prohibitively expensive, or rely on suboptimal ad hoc adaptation or augmentation approaches.

BRAIN IMAGE SEGMENTATION BRAIN SEGMENTATION FEW-SHOT SEMANTIC SEGMENTATION IMAGE REGISTRATION ZERO SHOT SEGMENTATION

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

29 Oct 2018arnab39/FewShot_GAN-Unet3D

In addition, our work presents a comprehensive analysis of different GAN architectures for semi-supervised segmentation, showing recent techniques like feature matching to yield a higher performance than conventional adversarial training approaches.

3D MEDICAL IMAGING SEGMENTATION BRAIN IMAGE SEGMENTATION BRAIN SEGMENTATION FEW-SHOT SEMANTIC SEGMENTATION SEMI-SUPERVISED SEMANTIC SEGMENTATION

FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation

29 Jul 2019HKUSTCV/FSS-1000

In this paper, we are interested in few-shot object segmentation where the number of annotated training examples are limited to 5 only.

FEW-SHOT SEMANTIC SEGMENTATION SEMANTIC SEGMENTATION

Adaptive Masked Proxies for Few-Shot Segmentation

19 Feb 2019MSiam/AdaptiveMaskedProxies

Our method is evaluated on PASCAL-$5^i$ dataset and outperforms the state-of-the-art in the few-shot semantic segmentation.

FEW-SHOT SEMANTIC SEGMENTATION SEMANTIC SEGMENTATION VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION