[1] [1] Yang Z, Yu H, Feng M, et al. Small object augmentation of urban scenes for real-time semantic segmentation [J]. IEEE Transactions on Image Processing, 2020, 29: 5175-5190.

[2] [2] Ge Y, Zhang R, Wang X, et al. Deepfashion2: A versatile benchmark for detection, pose estimation, segmentation and re-identification of clothing images [C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019: 5337-5345.

[5] [5] He K, Zhang X, Ren S, et al. Deep residual learning for image recognition [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 770-778.

[6] [6] Zhao H, Shi J, Qi X, et al. Pyramid scene parsing network [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 2881-2890.

[7] [7] Sun K, Zhao Y, Jiang B, et al. High-resolution representations for labeling pixels and regions [J]. arXiv preprint arXiv:1904.04514, 2019.

[8] [8] 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, 2017, 39(12): 2481-2495.

[9] [9] Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation [C]//Medical Image Computing and Computer - Assisted Intervention-MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. Springer International Publishing, 2015: 234-241.

[10] [10] Fu J, Liu J, Tian H, et al. Dual attention network for scene segmentation [C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019: 3146-3154.

[11] [11] Jiang Yuming, Yang Shuai, Qiu Haonan, Wu Wayne, Chen Change Loy, and Liu Ziwei. Text2human: Text-driven controllable human image generation. ACM Transactions on Graphics (TOG), 41(4):1-11, 2022.

[12] [12] Li X, You A, Zhu Z, et al. Semantic flow for fast and accurate scene parsing [C]//Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part I 16. Springer International Publishing, 2020: 775-793.

[13] [13] Yu C, Gao C, Wang J, et al. Bisenet v2: Bilateral network with guided aggregation for real-time semantic segmentation [J]. International Journal of Computer Vision, 2021, 129: 3051-3068.

[14] [14] Hong Y, Pan H, Sun W, et al. Deep dual-resolution networks for real-time and accurate semantic segmentation of road scenes [J]. arXiv preprint arXiv:2101.06085, 2021.

[15] [15] Ouyang D, He S, Zhang G, et al. Efficient Multi-Scale Attention Module with Cross - Spatial Learning [C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1-5.

[16] [16] Romera E, Alvarez J M, Bergasa L M, et al. Erfnet: Efficient residual factorized convnet for real-time semantic segmentation [J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 19(1): 263-272.

[17] [17] Poudel R P K, Liwicki S, Cipolla R. Fast-scnn: Fast semantic segmentation network [J]. arXiv preprint arXiv: 1902.04502, 2019.

[18] [18] Yu C, Wang J, Peng C, et al. Bisenet: Bilateral segmentation network for real-time semantic segmentation [C]//Proceedings of the European conference on computer vision (ECCV). 2018: 325-341.

[19] [19] Chen L C, Zhu Y, Papandreou G, et al. Encoder-decoder with atrous separable convolution for semantic image segmentation [C]//Proceedings of the European conference on computer vision (ECCV). 2018: 801-818.

[20] [20] Wu H, Zhang J, Huang K, et al. Fastfcn: Rethinking dilated convolution in the backbone for semantic segmentation [J]. arXiv preprint arXiv:1903.11816, 2019.