Real-Time and Accurate Semantic Segmentation Based on Separable Residual Modules

Wenchao Lu; Yanwei Pang; Yuqing He; Jian Wang

doi:10.3788/LOP56.051005

[1] Romera E, Bergasa L M. -07-04)[2018-08-10]. https:∥arxiv., org/abs/1607, 00971(2016).

[2] Li L H, Qian B, Lian J et al. Study on traffic scene semantic segmentation method based on convolutional neural network[J]. Journal on Communications, 39, 123-130(2018).

[3] Lecun Y, Bottou L, Bengio Y et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 86, 2278-2324(1998). http://ieeexplore.ieee.org/iel4/5/15641/00726791.pdf

[4] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017). http://dl.acm.org/citation.cfm?id=2999257

[5] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 3431-3440(2015).

[6] Fang X, Wang G H, Yang H C et al. High resolution remote sensing image classification combining with mean-shift segmentation and fully convolution neural network[J]. Laser & Optoelectronics Progress, 55, 022802(2018).

[7] Wang L, Liu Q. A multi-object image segmentation algorithm based on local features[J]. Laser & Optoelectronics Progress, 55, 061002(2018).

[8] Ji M Y, Xi X M, Yu Z L[J]. A review of semantic segmentation based on deep learning Information Technology and Informatization, 2017, 137-140.

[9] Zhao H S, Shi J P, Qi X J et al. Pyramid scene parsing network. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 6230-6239(2017).

[10] Chen L C, Papandreou G, Kokkinos I, fully connected CRFs[EB/OL] et al. -12-22)[2018-08-10]. https:∥arxiv., org/abs/1412, 7062(2014).

[11] Chen L C, Papandreou G, Kokkinos I et al. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 834-848(2018). http://europepmc.org/abstract/MED/28463186

[12] Lin G S, Milan A, Shen C H et al. RefineNet: multi-path refinement networks for high-resolution semantic segmentation. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 5168-5177(2017).

[13] Paszke A, Chaurasia A, Kim S et al. -06-07)[2018-08-10]. https:∥arxiv., org/abs/1606, 02147(2016).

[14] Yu C, Wang J, Peng Cet al. Bisenet: bilateral segmentation network for real-time semantic segmentation[J]. -08-02)[2018-08-13]. https:∥arxiv., org/abs/1808, 00897(2018).

[15] Iandola F N, Han S, Moskewicz M W, <0.5 MB model size[EB/OL] et al. -11-04)[2018-08-10]. https:∥arxiv.org/pdf/1602.07360v4.pdf.(2016).

[16] Guo C C, Yu F Q, Chen Y. Image semantic segmentation based on convolutional neural network feature and improved superpixel matching[J]. Laser & Optoelectronics Progress, 55, 081005(2018).

[17] Yao H B, Bian J W, Cong J W et al. Medical image segmentation model based on local sparse shape representation[J]. Laser & Optoelectronics Progress, 55, 051011(2018).

[18] Cordts M, Omran M, Ramos S et al. The cityscapes dataset. [C]∥CVPR Workshop on the Future of Datasets in Vision, 1, 3(2015).

[19] Cordts M, Omran M, Ramos S et al. The cityscapes dataset for semantic urban scene understanding. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 3213-3223(2016).

[20] Howard A G, Zhu M, Chen B et al. -04-17)[2018-08-11]. https:∥arxiv., org/abs/1704, 04861(2017).

[21] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1-9(2015).

[22] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 770-778(2016).

[23] Wu Z, Shen C. -04-15)[2018-08-11]. https:∥arxiv., org/abs/1604, 04339(2016).

[24] Giusti A, Cireşan D C, Masci J et al. Fast image scanning with deep max-pooling convolutional neural networks. [C]∥Proceedings of IEEE International Conference on Image Processing, 4034-4038(2013).

[25] Holschneider M, Kronland-Martinet R, Morlet J et al. A real-time algorithm for signal analysis with the help of the wavelet transform[M]. Berlin, Heidelberg: Springer, 286-297(1990).

[26] Sermanet P, Eigen D, Zhang X, detection using convolutional networks[EB/OL] et al. -02-24)[2018-08-12]. https:∥arxiv., org/abs/1312, 6229(2014).

[27] Badrinarayanan V, Kendall A, Cipolla R. SegNet: a deep convolutional encoder-decoder architecture for image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 2481-2495(2017). http://arxiv.org/abs/1511.00561v3

[28] Kendall A, Badrinarayanan V. -10-10) [2018-08-12]. https:∥arxiv., org/abs/1511, 02680(2016).