Image Semantic Segmentation Based on Combination of DeepLabV3+ and Attention Mechanism

Yunfei Qiu; Jinyan Wen

doi:10.3788/LOP202259.0410008

[1] Wang E D, Qi K, Li X P et al. Semantic segmentation of remote sensing image based on neural network[J]. Acta Optica Sinica, 39, 1210001(2019).

[2] Hu X X, Yang K L, Fei L et al. ACNET: attention based network to exploit complementary features for RGBD semantic segmentation[C], 1440-1444(2019).

[3] Zhang S, Li Y P. Retinal vascular image segmentation based on improved HED network[J]. Acta Optica Sinica, 40, 0610002(2020).

[4] Noh H, Hong S, Han B. Learning deconvolution network for semantic segmentation[C], 1520-1528(2015).

[5] Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 640-651(2017).

[6] Zhao H S, Shi J P, Qi X J et al. Pyramid scene parsing network[C], 6230-6239(2017).

[7] Wang P Q, Chen P F, Yuan Y et al. Understanding convolution for semantic segmentation[C], 1451-1460(2018).

[8] Tan G H, Hou J, Han Y P et al. Low-parameter real-time image segmentation algorithm based on convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 091003(2019).

[9] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[M]. Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention-MICCAI 2015, 9351, 234-241(2015).

[10] Chaurasia A, Culurciello E. LinkNet: exploiting encoder representations for efficient semantic segmentation[C], 17614349(2017).

[11] Tian Z, He T, Shen C H et al. Decoders matter for semantic segmentation: data-dependent decoding enables flexible feature aggregation[C], 3121-3130(2019).

[12] Wang F, Jiang M Q, Qian C et al. Residual attention network for image classification[C], 6450-6458(2017).

[13] Fu J L, Zheng H L, Mei T. Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition[C], 4476-4484(2017).

[14] Fu J, Liu J, Tian H J et al. Dual attention network for scene segmentation[C], 3141-3149(2019).

[15] Cao J X, Chen Q, Guo J et al. Attention-guided context feature pyramid network for object detection[EB/OL]. https://arxiv.org/abs/2005.11475v1

[16] Li H C, Xiong P F, An J et al. Pyramid attention network for semantic segmentation[EB/OL]. https://arxiv.org/abs/1805.10180

[17] Chen L C, Papandreou G, Kokkinos I et al. Semantic image segmentation with deep convolutional nets and fully connected CRFs[EB/OL]. https://arxiv.org/abs/1412.7062v2

[18] Chen L C, Papandreou G, Schroff F et al. Rethinking atrous convolution for semantic image segmentation[EB/OL]. https://arxiv.org/abs/1706.05587

[19] 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).

[20] Chen L C, Zhu Y K, Papandreou G et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018, 11211, 833-851(2018).

[21] Chollet F. Xception: deep learning with depthwise separable convolutions[C], 1800-1807(2017).

[22] Russakovsky O, Deng J, Su H et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 115, 211-252(2015).

[23] Abadi M, Agarwal A et al. TensorFlow: large-scale machine learning on heterogeneous distributed systems[EB/OL]. https://arxiv.org/abs/1603.04467

[24] Zhao T, Wu X Q. Pyramid feature attention network for saliency detection[C], 3080-3089(2019).

[25] Peng C, Zhang X Y, Yu G et al. Large kernel matters: improve semantic segmentation by global convolutional network[C], 1743-1751(2017).

[26] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 318-327(2020).

[27] Fu J, Liu J, Tian H J et al. Dual attention network for scene segmentation[C], 3141-3149(2019).

[28] Zhong Z L, Lin Z Q, Bidart R et al. Squeeze-and-attention networks for semantic segmentation[C], 13062-13071(2020).

[29] Xu C, Wang L. Image semantic segmentation method based on improved DeepLabv3+ network[J]. Laser & Optoelectronics Progress, 58, 1610008(2021).

[30] Liu W X, Shu Y Z, Tang X M et al. Remote sensing image segmentation using dual attention mechanism Deeplabv3+ algorithm[J]. Tropical Geography, 40, 303-313(2020).

[31] Ren F L, He X, Wei Z H et al. Semantic segmentation based on DeepLabV3+ and superpixel optimization[J]. Optics and Precision Engineering, 27, 2722-2729(2019).