Dilated cnn

Yu, Fisher, and Vladlen Koltun. "Multi-scale context aggregation by dilated convolutions." arXiv preprint arXiv:1511.07122 (2015).

• dense prediction : "The goal is to compute a discrete or continuous label for each pixel in the image.”
  • good example is semantic segmentation
    • multi-scale contextual reasoning? (He et al., 2004; Galleguillos & Belongie, 2010).
  • ref. Sercu, Tom, and Vaibhava Goel. "Dense Prediction on Sequences with Time-Dilated Convolutions for Speech Recognition." arXiv preprint arXiv:1611.09288 (2016).
  • (almost) prerequisite : Long, Jonathan, Evan Shelhamer, and Trevor Darrell. "Fully convolutional networks for semantic segmentation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
• The familiar discrete convolution is simply the 1-dilated convolution.
• ref. Dilated Convolutions and Kronecker Factored Convolutions ★
  • Kronecker product (wikipedia)
  • this ref is from reddit. Another links are there.

etc

• CRF : Chen, Liang-Chieh, et al. "Semantic image segmentation with deep convolutional nets and fully connected crfs." arXiv preprint arXiv:1412.7062 (2014).