[1] Yue S Y. Image semantic segmentation based on hierarchical context information[J]. Laser & Optoelectronics Progress, 56, 241005(2019).

[2] Li L K, Lu C H, Zou B. Research on target detection and feasible region segmentation based on deep learning[J]. Laser & Optoelectronics Progress, 57, 121013(2020).

[3] Liu W J, Wang F, Qu H C. Object detection model based on multi-scale feature integration[J]. Laser & Optoelectronics Progress, 56, 231007(2019).

[4] Goodfellow I J, Pouget-Abadie J, Mirza M et al. Generative adversarial nets. [C]//Proceedings of the 27th International Conference on Neural Information Prccessing Systems, December 7-12, 2014, Montreal, Quebec, Canada. New York: Curran Associates, 2, 2672-2680(2014).

[5] Chen X F, Shen H J, Bian Q et al. Face image super-resolution with an attention mechanism[J]. Journal of Xidian University (Natural Science), 46, 148-153(2019).

[6] Reed S, Akata Z, Yan X C et al. -06-05)[2020-05-28], org/abs/1605, 05396(2016). https://arxiv.

[7] Mirza M. -11-06)[2020-05-28][EB/OL]. Osindero S. Conditional generative adversarial nets., org/abs/1411, 1784(2014). https://arxiv.

[8] [8] ZhangH, XuT, Li HS, et al.StackGAN: text to photo-realistic image synthesis with stacked generative adversarial networks[C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE Press, 2017: 5908- 5916.

[9] Zhang H, Xu T, Li H S et al. StackGAN++: realistic image synthesis with stacked generative adversarial networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 1947-1962(2019). http://ieeexplore.ieee.org/document/8411144/citations?tabFilter=papers

[10] [10] XuT, Zhang PC, Huang QY, et al.AttnGAN: fine-grained text to image generation with attentional generative adversarial networks[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE Press, 2018: 1316- 1324.

[11] Johnson J, Gupta A, Fei-Fei L. Image generation from scene graphs[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 1219-1228(2018).

[12] Ashual O, Wolf L. Specifying object attributes and relations in interactive scene generation[C]//2019 IEEE/CVF International Conference on Computer Vision (ICCV), October 27 - November 2, 2019, Seoul, Korea (South)., 4560-4568(2019).

[13] Luo J, Huang J Y. Generative adversarial network: an overview[J]. Chinese Journal of Scientific Instrument, 40, 74-84(2019).

[14] Chen Q F, Koltun V. Photographic image synthesis with cascaded refinement networks[C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 1520-1529(2017).

[15] Krishna R, Zhu Y K, Groth O et al. Visual genome: connecting language and vision using crowdsourced dense image annotations[J]. International Journal of Computer Vision, 123, 32-73(2017). http://dl.acm.org/doi/abs/10.1007/s11263-016-0981-7

[16] Hu R H, Dollár P, He K M et al. Learning to segment every thing[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 4233-4241(2018).

[17] He K M, Gkioxari G, Dollár P et al. Mask R-CNN[C]//2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 2980-2988(2017).

[18] Wang T C, Liu M Y, Zhu J Y et al. High-resolution image synthesis and semantic manipulation with conditional GANs[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 8798-8807(2018).

[19] Salimans T, Goodfellow I, Zaremba W et al. -06-10)[2020-05-28], org/abs/1606, 03498(2016). https://arxiv.

[20] Heusel M, Ramsauer H, Unterthiner T et al. -01-12)[2020-05-28], org/abs/1706, 08500(2018). https://arxiv.