Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

@article{Zhang2017AmuletAM,
  title={Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection},
  author={Pingping Zhang and D. Wang and Huchuan Lu and Hongyu Wang and Xiang Ruan},
  journal={2017 IEEE International Conference on Computer Vision (ICCV)},
  year={2017},
  pages={202-211}
}
Fully convolutional neural networks (FCNs) have shown outstanding performance in many dense labeling problems. [] Key Method Our framework first integrates multi-level feature maps into multiple resolutions, which simultaneously incorporate coarse semantics and fine details. Then it adaptively learns to combine these feature maps at each resolution and predict saliency maps with the combined features. Finally, the predicted results are efficiently fused to generate the final saliency map.
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Methods Citations
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