{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:22:32Z","timestamp":1775470952529,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T00:00:00Z","timestamp":1663891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,9,23]]},"DOI":"10.1145\/3573942.3573980","type":"proceedings-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T23:45:42Z","timestamp":1684280742000},"page":"988-994","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["A Review of Research Based on Generative Adversarial Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0811-8930","authenticated-orcid":false,"given":"Tianyi","family":"Zhu","sequence":"first","affiliation":[{"name":"Xi'an University of Posts & Telecommunications, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9403-9699","authenticated-orcid":false,"given":"Huan","family":"Liu","sequence":"additional","affiliation":[{"name":"Xi'an University of Posts & Telecommunications, China"}]}],"member":"320","published-online":{"date-parts":[[2023,5,16]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"36322","article-title":"Recent progress on generative adversarial networks ( GANs): A survey [J]","volume":"2019","author":"Pan Z","unstructured":"Pan Z, Yu w, Yi X, Recent progress on generative adversarial networks ( GANs): A survey [J]. IEEE Access.2019, 7: 36322-36333.","journal-title":"IEEE Access"},{"key":"e_1_3_2_1_2_1","first-page":"2672","article-title":"Generative adversarial nets [C]\/ \/Advances","volume":"2014","author":"Goodfellow I","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Generative adversarial nets [C]\/ \/Advances in Neural Information Processing Systems, 2014: 2672-2680.","journal-title":"Neural Information Processing Systems"},{"issue":"7","key":"e_1_3_2_1_3_1","first-page":"1220","volume":"15","author":"Ns Based Privacy Amplification","year":"2021","unstructured":"LI X M, WU J R, WU S Q.GANs Based Privacy Amplification Against Bounded Adversaries[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(7): 1220-1226.","journal-title":"Journal of Frontiers of Computer Science and Technology"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01753433"},{"issue":"3","key":"e_1_3_2_1_5_1","first-page":"377","article-title":"Survey on research progress of generating adversarial networks [J]","volume":"14","author":"Wu SQ","year":"2020","unstructured":"Wu SQ, Li XM. Survey on research progress of generating adversarial networks [J]. Journal of Frontiers of Computer Science and Technology, 2020, 14 (3): 377-388.","journal-title":"Journal of Frontiers of Computer Science and Technology"},{"key":"e_1_3_2_1_6_1","volume-title":"Discovering future malware variants by generating new malware samples using generative adversarial network [C] \/\/9th International Conference on Computer and Knowledge Engineering","author":"Moti Z","year":"2019","unstructured":"Moti Z, Hashemi S, Namavar A. Discovering future malware variants by generating new malware samples using generative adversarial network [C] \/\/9th International Conference on Computer and Knowledge Engineering, 2019: 319-324."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301282"},{"key":"e_1_3_2_1_8_1","volume-title":"Semantic segmentation using adversarial networks[J]. arXiv preprint arXiv:1611.08408","author":"Luc P","year":"2016","unstructured":"Luc P, Couprie C, Chintala S, Semantic segmentation using adversarial networks[J]. arXiv preprint arXiv:1611.08408, 2016."},{"key":"e_1_3_2_1_9_1","unstructured":"Salimans T Goodfellow I Zaremba W Improved techniques for training GANs [EB\/OI] . 2016-06-10 [2017-12-05]. https:\/\/ arxiv. org\/ pdf \/1606.03498. pdf."},{"key":"e_1_3_2_1_10_1","unstructured":"Mirza M Osindero S. Conditional generative adversarial nets[J]. arXiv:1411.1784 2014."},{"key":"e_1_3_2_1_11_1","volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks computer science[J]. arXiv:1511.06434","author":"Zhu W","year":"2015","unstructured":"Zhu W, Miao J, Qing L, Unsupervised representation learning with deep convolutional generative adversarial networks computer science[J]. arXiv:1511.06434, 2015."},{"key":"e_1_3_2_1_12_1","volume-title":"Montreal","author":"Denton E","year":"2015","unstructured":"Denton E, Chintala S, Szlam A, Deep generative image models using a Laplacian pyramid of adversarial networks[C]\/\/Proceedings of the 28th International Conference on Neural Information Processing Systems, Montreal, Dec 7-12, 2015. Cambridge: MIT Press, 2015: 1486-1494."},{"key":"e_1_3_2_1_13_1","volume-title":"InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets[J]","author":"Chen X","year":"2016","unstructured":"Chen X, Duan Y, Houthooft R, InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets[J]. 2016."},{"key":"e_1_3_2_1_14_1","unstructured":"Arjovsky M Chintala S Bottou L. Wasserstein GAN[J]. 2017."},{"key":"e_1_3_2_1_15_1","volume-title":"Improved Training of Wasserstein GANs[J]","author":"Gulrajani I","year":"2017","unstructured":"Gulrajani I, Ahmed F, Arjovsky M, Improved Training of Wasserstein GANs[J]. 2017."},{"key":"e_1_3_2_1_16_1","volume-title":"Metz L. BEGAN: Boundary Equilibrium Generative Adversarial Networks[J]","author":"Berthelot D","year":"2017","unstructured":"Berthelot D, Schumm T, Metz L. BEGAN: Boundary Equilibrium Generative Adversarial Networks[J]. 2017."},{"key":"e_1_3_2_1_17_1","volume-title":"Least Squares Generative Adversarial Networks[J]","author":"Mao X","year":"2016","unstructured":"Mao X, Li Q, Xie H, Least Squares Generative Adversarial Networks[J]. 2016."},{"key":"e_1_3_2_1_18_1","volume-title":"Large scale GAN training for high fidelity natural image synthesis[J]. arXiv:1809.11096","author":"Brock A","year":"2018","unstructured":"Brock A, Donahue J, Simonyan K. Large scale GAN training for high fidelity natural image synthesis[J]. arXiv:1809.11096, 2018."},{"key":"e_1_3_2_1_19_1","first-page":"5967","volume-title":"Honolulu","author":"Isola P","year":"2017","unstructured":"Isola P, Zhu J Y, Zhou T H, Image-to-image translation with conditional adversarial networks[C]\/Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, Jul 21-26, 2017. Washington: IEEE Computer Society, 2017: 5967-5976."},{"key":"e_1_3_2_1_20_1","first-page":"2242","volume-title":"Venice","author":"Zhu J Y","year":"2017","unstructured":"Zhu J Y, Pakr T, Isola P, Unpaired image-to-image translation using cycle consistent adversarial networks[C]\/\/Proceedings of the 2017 IEEE International Conference on Computer Vision, Venice, Oct 22-29, 2017. Washington: IEEE Computer Society, 2017: 2242-2251."},{"key":"e_1_3_2_1_21_1","volume-title":"Photo realistic single image superre solution using a generative adversarial net-work[J]. arXiv:1609.04802","author":"Ledig C","year":"2016","unstructured":"Ledig C, Theis L, Huszar F, Photo realistic single image superre solution using a generative adversarial net-work[J]. arXiv:1609.04802, 2016."},{"key":"e_1_3_2_1_22_1","volume-title":"Generating images with perceptual similarity metrics based on deep networks[J]. arXiv:1602.02644","author":"Alexey D","year":"2016","unstructured":"Alexey D, Brox T. Generating images with perceptual similarity metrics based on deep networks[J]. arXiv:1602.02644, 2016."},{"key":"e_1_3_2_1_23_1","first-page":"1060","article-title":"Generative adversarial text to image synthesis[C]\/\/International Conference on International Conference on Machine Learning","volume":"2016","unstructured":"REED S, AKATA Z, YAN X, Generative adversarial text to image synthesis[C]\/\/International Conference on International Conference on Machine Learning. JMLR. org, 2016:1060-1069.","journal-title":"JMLR. org"},{"key":"e_1_3_2_1_24_1","volume-title":"Adversarial Audio Synthesis[J]. arXiv:1802.04208","author":"Donahue J","year":"2018","unstructured":"C Donahue, J Mcauley, M Puckette. Adversarial Audio Synthesis[J]. arXiv:1802.04208, 2018."},{"key":"e_1_3_2_1_25_1","volume-title":"StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation[J]","author":"Choi Y","year":"2017","unstructured":"Choi Y, Choi M, Kim M, StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation[J]. 2017."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.241]"},{"key":"e_1_3_2_1_27_1","volume-title":"Salt Lake City, Jun 18-22,2018. Washington","author":"Chen Y S","year":"2018","unstructured":"Chen Y S, Wei W, Liang W, Multistage adversarial losses for pose based human image synthesis[C] \/\/ Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun 18-22,2018. Washington: IEEE Computer Society, 2018: 118-126."},{"key":"e_1_3_2_1_28_1","volume-title":"Salt Lake City, Jun18-22","author":"Gupta A","year":"2018","unstructured":"Gupta A, Johnson J, Li F F, Social GAN: socially acceptable trajectories with generative adversarial networks[C]\/\/Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun18-22, 2018. Washington: IEEE Computer Society,2018:2255-2264."},{"key":"e_1_3_2_1_29_1","first-page":"6713","volume-title":"Salt Lake City","author":"Jian M B","year":"2018","unstructured":"Jian M B, Dong C, Fang W, Towards open set identity preserving face synthesis[C] \/\/ Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun 18-22, 2018. Washington: IEEE Computer Society, 2018: 6713-6722."},{"key":"e_1_3_2_1_30_1","volume-title":"Salt Lake City, Jun 18-22,2018. Washington","author":"Guo Z P","year":"2018","unstructured":"Guo Z P, Shang F W. Weakly supervised facial action unit recognition through adversarial training[C] \/\/ Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun 18-22,2018. Washington: IEEE Computer Society, 2018: 2188-2196."},{"key":"e_1_3_2_1_31_1","volume-title":"Salt Lake City, Jun 18-22,2018. Washington","author":"Hong Y Y","year":"2018","unstructured":"Hong Y Y, Di H, Yun H W, Learning face age progression: a pyramid architecture of GANs[C] \/\/ Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun 18-22,2018. Washington: IEEE Computer Society, 2018: 31-39."},{"key":"e_1_3_2_1_32_1","unstructured":"Mathieu M Couprie C LeCun Y. Deep multi-scale video prediction beyond mean square error [EB\/OL]. 2016-02-26 [2017-1219]. https:\/\/arxiv.org\/pdf\/1511. 05440. pdf."},{"key":"e_1_3_2_1_33_1","unstructured":"Choi E Biswal S Malin B Generating Multi-label discrete electronic health records using generative adversarial network [EB\/OL]. 2018-01-11 [2018-01-28]. https:\/\/arxiv. org\/pdf\/1703.06490v1. pdf."},{"key":"e_1_3_2_1_34_1","volume-title":"Salt Lake City","author":"Zi Z Z","year":"2018","unstructured":"Zi Z Z, Lin Y, Ye F Z. Translating and segmenting multi-modal medical volumes with cycle and shape-consistency generative adversarial network[C]\/\/Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, Jun 18-22, 2018. Washington: IEEE Computer Society, 2018: 9242-9251."},{"issue":"6","key":"e_1_3_2_1_35_1","first-page":"173","article-title":"Motion blurred image restoration based on generating confrontation network[J]","volume":"55","author":"Sang L","year":"2019","unstructured":"Sang L, Gao S, Yin Z S. Motion blurred image restoration based on generating confrontation network[J]. Computer Engineering and Applications, 2019, 55(6): 173-177.","journal-title":"Computer Engineering and Applications"},{"issue":"8","key":"e_1_3_2_1_36_1","first-page":"1402","article-title":"Application of generating confrontation network in image completion[J]","volume":"13","author":"Shi C","year":"2019","unstructured":"Shi C, Pan B, Guo X M, Application of generating confrontation network in image completion[J]. Journal of Frontiers of Computer Science and Technology, 2019, 13(8): 1402-1410.","journal-title":"Journal of Frontiers of Computer Science and Technology"}],"event":{"name":"AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","location":"Xiamen China","acronym":"AIPR 2022"},"container-title":["Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3573942.3573980","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3573942.3573980","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:31Z","timestamp":1750186951000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3573942.3573980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,23]]},"references-count":36,"alternative-id":["10.1145\/3573942.3573980","10.1145\/3573942"],"URL":"https:\/\/doi.org\/10.1145\/3573942.3573980","relation":{},"subject":[],"published":{"date-parts":[[2022,9,23]]},"assertion":[{"value":"2023-05-16","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}