Fully Convolutional Networks for Semantic Segmentation

@article{Shelhamer2017FullyCN,
  title={Fully Convolutional Networks for Semantic Segmentation},
  author={Evan Shelhamer and Jonathan Long and Trevor Darrell},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2017},
  volume={39},
  pages={640-651}
}
Convolutional networks are powerful visual models that yield hierarchies of features. [...] Key Method We define and detail the space of fully convolutional networks, explain their application to spatially dense prediction tasks, and draw connections to prior models. We adapt contemporary classification networks (AlexNet, the VGG net, and GoogLeNet) into fully convolutional networks and transfer their learned representations by fine-tuning to the segmentation task.Expand
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