{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T12:02:31Z","timestamp":1725624151906},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,4,23]]},"DOI":"10.1145\/3404555.3404597","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T13:00:58Z","timestamp":1597928458000},"page":"374-379","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["ECycleGAN"],"prefix":"10.1145","author":[{"given":"Xianchao","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Software, Dalian University of Technology, Dalian, China"}]},{"given":"Changjia","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Software, Dalian University of Technology, Dalian, China"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 1125--1134","author":"Isola P.","key":"e_1_3_2_1_1_1","unstructured":"Isola , P. , Zhu , J. Y. , and Zhou , T . 2017. Image-to-image translation with conditional adversarial network . Proceedings of the IEEE conference on computer vision and pattern recognition, 1125--1134 . Isola, P., Zhu, J. Y., and Zhou, T.2017. Image-to-image translation with conditional adversarial network. Proceedings of the IEEE conference on computer vision and pattern recognition, 1125--1134."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00845"},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 770--778","author":"He K.","key":"e_1_3_2_1_3_1","unstructured":"He , K. , Zhang , X. , and Ren , S . 2016. Deep residual learning for image recognition . Proceedings of the IEEE conference on computer vision and pattern recognition, 770--778 . He, K., Zhang, X., and Ren, S. 2016. Deep residual learning for image recognition. Proceedings of the IEEE conference on computer vision and pattern recognition, 770--778."},{"key":"e_1_3_2_1_4_1","unstructured":"Taigman Y. Polyak A. and Wolf L. 2016. Unsupervised cross-domain image generation. arXiv preprint arXiv:1611.02200. Taigman Y. Polyak A. and Wolf L. 2016. Unsupervised cross-domain image generation. arXiv preprint arXiv:1611.02200."},{"key":"e_1_3_2_1_5_1","unstructured":"Goodfellow I. Pouget-Abadie J. and Mirza M. 2014. Generative adversarial nets[C]\/\/Advances in neural information processing systems 2672--2680. 10.5555\/2969033.2969125 Goodfellow I. Pouget-Abadie J. and Mirza M. 2014. Generative adversarial nets[C]\/\/Advances in neural information processing systems 2672--2680. 10.5555\/2969033.2969125"},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 1646--1654","author":"Kim J.","key":"e_1_3_2_1_6_1","unstructured":"Kim , J. , Kwon , L. J. , and Mu , L. K . 2016. Accurate image super-resolution using very deep convolutional networks . Proceedings of the IEEE conference on computer vision and pattern recognition, 1646--1654 . Kim, J., Kwon, L. J., and Mu, L. K. 2016. Accurate image super-resolution using very deep convolutional networks. Proceedings of the IEEE conference on computer vision and pattern recognition, 1646--1654."},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 2414--2423","author":"Gatys L. A.","key":"e_1_3_2_1_7_1","unstructured":"Gatys , L. A. , Ecker , A. S. , and Bethge , M . 2016. Image style transfer using convolutional neural networks . Proceedings of the IEEE conference on computer vision and pattern recognition, 2414--2423 . Gatys, L. A., Ecker, A. S., and Bethge, M. 2016. Image style transfer using convolutional neural networks. Proceedings of the IEEE conference on computer vision and pattern recognition, 2414--2423."},{"volume-title":"U-net: Convolutional networks for biomedical image segmentation. International Conference on Medical image computing and computer-assisted intervention","year":"2015","author":"Ronneberger O.","key":"e_1_3_2_1_8_1","unstructured":"Ronneberger , O. , Fischer , P. , and Brox , T . 2015 . U-net: Convolutional networks for biomedical image segmentation. International Conference on Medical image computing and computer-assisted intervention , Springer , Cham , 234--241. Ronneberger, O., Fischer, P., and Brox, T. 2015. U-net: Convolutional networks for biomedical image segmentation. International Conference on Medical image computing and computer-assisted intervention, Springer, Cham, 234--241."},{"key":"e_1_3_2_1_9_1","unstructured":"Denton E. L. Chintala S. and Fergus R. 2015. Deep generative image models using a laplacian pyramid of adversarial networks[C]\/\/Advances in neural information processing systems 1486--1494. 10.5555\/2969239.2969405 Denton E. L. Chintala S. and Fergus R. 2015. Deep generative image models using a laplacian pyramid of adversarial networks[C]\/\/Advances in neural information processing systems 1486--1494. 10.5555\/2969239.2969405"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Pathak D. Krahenbuhl P. and Donahue J. 2016. Context encoders: Feature learning by inpainting[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition 2536--2544. Pathak D. Krahenbuhl P. and Donahue J. 2016. Context encoders: Feature learning by inpainting[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition 2536--2544.","DOI":"10.1109\/CVPR.2016.278"},{"key":"e_1_3_2_1_11_1","unstructured":"Liu M. Y. Breuel T. and Kautz J. 2017. Unsupervised image-to-image translation. Advances in neural information processing systems 700--708. 10.5555\/3294771.3294838 Liu M. Y. Breuel T. and Kautz J. 2017. Unsupervised image-to-image translation. Advances in neural information processing systems 700--708. 10.5555\/3294771.3294838"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073659"},{"key":"e_1_3_2_1_13_1","unstructured":"Radford A. Metz L. and Chintala S. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434. Radford A. Metz L. and Chintala S. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434."},{"volume-title":"Proceedings of the IEEE international conference on computer vision, 2223--2232","author":"Zhu J. Y.","key":"e_1_3_2_1_14_1","unstructured":"Zhu , J. Y. , Park , T. , and Isola , P . 2017. Unpaired image-to-image translation using cycle-consistent adversarial networks . Proceedings of the IEEE international conference on computer vision, 2223--2232 . Zhu, J. Y., Park, T., and Isola, P. 2017. Unpaired image-to-image translation using cycle-consistent adversarial networks. Proceedings of the IEEE international conference on computer vision, 2223--2232."},{"key":"e_1_3_2_1_15_1","unstructured":"Goodfellow I. Pouget-Abadie and J. Mirza M. 2014. Generative adversarial nets. Advances in neural information processing systems 2672--2680. 10.5555\/2969033.2969125 Goodfellow I. Pouget-Abadie and J. Mirza M. 2014. Generative adversarial nets. Advances in neural information processing systems 2672--2680. 10.5555\/2969033.2969125"},{"key":"e_1_3_2_1_16_1","unstructured":"Liu M. Y. and Tuzel O. 2016. Coupled generative adversarial networks. Advances in neural information processing systems 469--477. 10.5555\/3157096.3157149 Liu M. Y. and Tuzel O. 2016. Coupled generative adversarial networks. Advances in neural information processing systems 469--477. 10.5555\/3157096.3157149"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Dong C. Loy C. C. and He K. 2015. Image super-resolution using deep convolutional networks. IEEE transactions on pattern analysis and machine intelligence 38(2): 295--307. 10.1109\/TPAMI.2015.2439281 Dong C. Loy C. C. and He K. 2015. Image super-resolution using deep convolutional networks. IEEE transactions on pattern analysis and machine intelligence 38(2): 295--307. 10.1109\/TPAMI.2015.2439281","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"e_1_3_2_1_18_1","unstructured":"Zhang R. Zhu J. Y. and Isola P. 2017. Real-time user-guided image colorization with learned deep priors. arXiv preprint arXiv:1705.02999. 10.1145\/3072959.3073703 Zhang R. Zhu J. Y. and Isola P. 2017. Real-time user-guided image colorization with learned deep priors. arXiv preprint arXiv:1705.02999. 10.1145\/3072959.3073703"},{"key":"e_1_3_2_1_19_1","unstructured":"Kingma D. P. and Welling M. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114. Kingma D. P. and Welling M. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114."},{"key":"e_1_3_2_1_20_1","unstructured":"Dumoulin V. Belghazi I. and Poole B. 2016. Adversarially learned inference. arXiv preprint arXiv:1606.00704. Dumoulin V. Belghazi I. and Poole B. 2016. Adversarially learned inference. arXiv preprint arXiv:1606.00704."},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 8798--8807","author":"Wang T. C.","key":"e_1_3_2_1_21_1","unstructured":"Wang , T. C. , Liu , M. Y. , and Zhu , J. Y . 2018. High-resolution image synthesis and semantic manipulation with conditional gans . Proceedings of the IEEE conference on computer vision and pattern recognition, 8798--8807 . Wang, T. C., Liu, M. Y., and Zhu, J. Y. 2018. High-resolution image synthesis and semantic manipulation with conditional gans. Proceedings of the IEEE conference on computer vision and pattern recognition, 8798--8807."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295301"},{"volume-title":"Proceedings of the IEEE International Conference on Computer Vision, 1501--1510","author":"Huang X.","key":"e_1_3_2_1_23_1","unstructured":"Huang , X. , and Belongie , S . 2017. Arbitrary style transfer in real-time with adaptive instance normalization . Proceedings of the IEEE International Conference on Computer Vision, 1501--1510 . Huang, X., and Belongie, S. 2017. Arbitrary style transfer in real-time with adaptive instance normalization. Proceedings of the IEEE International Conference on Computer Vision, 1501--1510."},{"volume-title":"Proceedings of the European conference on computer vision (ECCV), 35--51","author":"Lee H. Y.","key":"e_1_3_2_1_24_1","unstructured":"Lee , H. Y. , Tseng , H. Y. , and Huang , J. B . 2018. Diverse image-to-image translation via disentangled representations . Proceedings of the European conference on computer vision (ECCV), 35--51 . Lee, H. Y., Tseng, H. Y., and Huang, J. B. 2018. Diverse image-to-image translation via disentangled representations. Proceedings of the European conference on computer vision (ECCV), 35--51."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"volume-title":"Proceedings of the 34th International Conference on Machine Learning-Volume 70","year":"1857","author":"Kim T.","key":"e_1_3_2_1_26_1","unstructured":"Kim , T. , Cha , M. , and Kim , H . 2017. Learning to discover cross-domain relations with generative adversarial networks . Proceedings of the 34th International Conference on Machine Learning-Volume 70 .JMLR. org, 1857 --1865. 10.5555\/3305381.3305573 Kim, T., Cha, M., and Kim, H. 2017. Learning to discover cross-domain relations with generative adversarial networks. Proceedings of the 34th International Conference on Machine Learning-Volume 70.JMLR. org, 1857--1865. 10.5555\/3305381.3305573"},{"key":"e_1_3_2_1_27_1","unstructured":"Simonyan K. and Zisserman A. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556. Simonyan K. and Zisserman A. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556."},{"key":"e_1_3_2_1_28_1","unstructured":"Zhu J. Y. Zhang R. and Pathak D. 2017. Toward multimodal image-to-image translation. Advances in neural information processing systems 465--476. 10.5555\/3294771.3294816 Zhu J. Y. Zhang R. and Pathak D. 2017. Toward multimodal image-to-image translation. Advances in neural information processing systems 465--476. 10.5555\/3294771.3294816"},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 3213--3223","author":"Cordts M.","key":"e_1_3_2_1_29_1","unstructured":"Cordts , M. , Omran , M. , and Ramos , S . 2016. The cityscapes dataset for semantic urban scene understanding . Proceedings of the IEEE conference on computer vision and pattern recognition, 3213--3223 . Cordts, M., Omran, M., and Ramos, S. 2016. The cityscapes dataset for semantic urban scene understanding. Proceedings of the IEEE conference on computer vision and pattern recognition, 3213--3223."},{"volume-title":"European conference on computer vision. Springer, Cham, 649--666","author":"Zhang R.","key":"e_1_3_2_1_30_1","unstructured":"Zhang , R. , Isola , P. , and Efros , A. A . 2016. Colorful image colorization . European conference on computer vision. Springer, Cham, 649--666 . Zhang, R., Isola, P., and Efros, A. A. 2016. Colorful image colorization. European conference on computer vision. Springer, Cham, 649--666."},{"key":"e_1_3_2_1_31_1","unstructured":"Krizhevsky A. Sutskever I. and Hinton G. E. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 1097--1105. 10.5555\/2999134.2999257 Krizhevsky A. Sutskever I. and Hinton G. E. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 1097--1105. 10.5555\/2999134.2999257"}],"event":{"name":"ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence","sponsor":["University of Tsukuba University of Tsukuba"],"location":"Tianjin China","acronym":"ICCAI '20"},"container-title":["Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404555.3404597","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,14]],"date-time":"2023-01-14T03:24:22Z","timestamp":1673666662000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404555.3404597"}},"subtitle":["Enhanced Cycle-Consistent Generative Adversarial Networks"],"short-title":[],"issued":{"date-parts":[[2020,4,23]]},"references-count":31,"alternative-id":["10.1145\/3404555.3404597","10.1145\/3404555"],"URL":"http:\/\/dx.doi.org\/10.1145\/3404555.3404597","relation":{},"subject":[],"published":{"date-parts":[[2020,4,23]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}
