SCIENCE CHINA Information Sciences, Volume 62 , Issue 12 : 227101(2019) https://doi.org/10.1007/s11432-019-2685-1

An open-source project for real-time image semantic segmentation

More info
  • ReceivedJul 22, 2019
  • AcceptedOct 7, 2019
  • PublishedOct 28, 2019


There is no abstract available for this article.


[1] Geng Q C, Zhou Z, Cao X C. Survey of recent progress in semantic image segmentation with CNNs. Sci China Inf Sci, 2018, 61: 051101 CrossRef Google Scholar

[2] Li X L, Shi J H, Dong Y S. A survey on scene image classification. Sci Sin Info, 2015, 45: 827-848 CrossRef Google Scholar

[3] Zhao H S, Shi J P, Qi X J, et al. Pyramid scene parsing network. In: Proceedings of CVPR, 2016. 6230--6239. Google Scholar

[4] Szegedy C, Vanhoucke V, Ioffe S, et al. Rethinking the inception architecture for computer vision. In: Proceedings of CVPR, 2016. 2818--2826. Google Scholar

[5] Ma N N, Zhang X Y, ZHeng H T, et al. ShuffleNet V2: practical guidelines for efficient CNN architecture design. In: Proceedings of ECCV, 2018. 122--138. Google Scholar

[6] Hu J, Shen L, Sun G, et al. Squeeze-and-excitation networks. In: Proceedings of CVPR, 2018. 7132--7141. Google Scholar

[7] Cordts M, Omran M, Ramos S, et al. The cityscapes dataset for semantic urban scene understanding. In: Proceedings of CVPR, 2016. 3213--3223. Google Scholar

[8] Howard A G, Zhu M L, Chen B, et al. Mobilenets: efficient convolutional neural networks for mobile vision applications. 2017,. arXiv Google Scholar

[9] Badrinarayanan V, Kendall A, Cipolla R. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.. IEEE Trans Pattern Anal Mach Intell, 2017, 39: 2481-2495 CrossRef PubMed Google Scholar

[10] Paszke A, Chaurasia A, Kim S, et al. Enet: a deep neural network architecture for real-time semantic segmentation. 2016,. arXiv Google Scholar

  • Figure 1

    (Color online) The overall asymmetric architecture of the proposed LEDNet. The encoder employs an FCN-like network, while an attention pyramid network is adopted in the decoder.