Laplacian Reconstruction and Refinement for Semantic Segmentation

@article{Ghiasi2016LaplacianRA,
  title={Laplacian Reconstruction and Refinement for Semantic Segmentation},
  author={Golnaz Ghiasi and Charless C. Fowlkes},
  journal={CoRR},
  year={2016},
  volume={abs/1605.02264}
}
CNN architectures have terrific recognition performance but rely on spatial pooling which makes it difficult to adapt them to tasks that require dense pixel-accurate labeling. This paper makes two contributions: (1) We demonstrate that while the apparent spatial resolution of convolutional feature maps is low, the high-dimensional feature representation contains significant sub-pixel localization information. (2) We describe a multi-resolution reconstruction architecture, akin to a Laplacian… CONTINUE READING

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