An overview of the proposed system for semi-supervised semantic image segmentation, where the segmentation network G outputs a class probability map, SA ...
The application of semi-supervised semantic image segmentation can effectively reduce the number of manually generated labels required in the training process.
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Jul 1, 2021 · The application of adversarial learning for semi-supervised semantic image segmentation based on convolutional neural networks can effectively ...
The proposed stable self-attention adversarial learning semi-supervised semantic image segmentation network is demonstrated to provide superior image ...
Semantic Scholar extracted view of "Stable self-attention adversarial learning for semi-supervised semantic image segmentation" by Jia Zhang et al.
The self-attention module selectively aggregates the features at each ... stability of the training. Our method has better performance than existing full/semi- ...
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A novel GAN framework comprised of a generator network and a dual discriminator network is proposed, and the entire network is trained by coupling the ...
Feb 22, 2018 · We propose a method for semi-supervised semantic segmentation using an adversarial network. While most existing discriminators are trained to ...
Missing: Stable self- attention
We propose a method for semi-supervised semantic segmentation using the adversarial network. While most existing discriminators are trained to classify ...