{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:29:56Z","timestamp":1742912996926,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030007669"},{"type":"electronic","value":"9783030007676"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-00767-6_40","type":"book-chapter","created":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T07:54:58Z","timestamp":1537257298000},"page":"430-440","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Coupled Learning for Image Generation and Latent Representation Inference Using MMD"],"prefix":"10.1007","author":[{"given":"Sheng","family":"Qian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen-ming","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Si","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hau-san","family":"Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,19]]},"reference":[{"key":"40_CR1","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein GAN. CoRR arXiv:1701.07875 (2017)"},{"key":"40_CR2","unstructured":"Bojanowski, P., Joulin, A., Lopez-Paz, D., Szlam, A.: Optimizing the latent space of generative networks. CoRR arXiv:1707.05776"},{"key":"40_CR3","unstructured":"Chen, X., et al.: Variational lossy autoencoder. CoRR arXiv:1611.02731 (2016)"},{"key":"40_CR4","unstructured":"Denton, E.L., Chintala, S., Szlam, A., Fergus, R.: Deep generative image models using a laplacian pyramid of adversarial networks. In: NIPS, pp. 1486\u20131494 (2015)"},{"key":"40_CR5","unstructured":"Dosovitskiy, A., Brox, T.: Generating images with perceptual similarity metrics based on deep networks. In: NIPS, pp. 658\u2013666 (2016)"},{"key":"40_CR6","unstructured":"Dumoulin, V., et al.: Adversarially learned inference. CoRR arXiv:1606.00704 (2016)"},{"key":"40_CR7","unstructured":"Dziugaite, G.K., Roy, D.M., Ghahramani, Z.: Training generative neural networks via maximum mean discrepancy optimization. In: UAI, pp. 258\u2013267 (2015)"},{"key":"40_CR8","unstructured":"Goodfellow, I.J., et al.: Generative adversarial nets. In: NIPS, pp. 2672\u20132680 (2014)"},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"Gretton, A., Borgwardt, K.M., Rasch, M.J., Sch\u00f6lkopf, B., Smola, A.J.: A kernel method for the two-sample-problem. In: NIPS, pp. 513\u2013520 (2006)","DOI":"10.7551\/mitpress\/7503.003.0069"},{"key":"40_CR10","unstructured":"Grewal, K., Hjelm, R.D., Bengio, Y.: Variance regularizing adversarial learning. CoRR arXiv:1707.00309"},{"key":"40_CR11","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: CVPR, pp. 5967\u20135976 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"40_CR12","unstructured":"Kim, T., Cha, M., Kim, H., Lee, J.K., Kim, J.: Learning to discover cross-domain relations with generative adversarial networks. In: ICML, pp. 1857\u20131865 (2017)"},{"key":"40_CR13","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. CoRR arXiv:1412.6980"},{"key":"40_CR14","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. CoRR arXiv:1312.6114"},{"key":"40_CR15","unstructured":"Krizhevsky, A., Hinton, G.: Learning multiple layers of features from tiny images (2009)"},{"key":"40_CR16","unstructured":"Larsen, A.B.L., S\u00f8nderby, S.K., Larochelle, H., Winther, O.: Autoencoding beyond pixels using a learned similarity metric. In: ICML, pp. 1558\u20131566 (2016)"},{"key":"40_CR17","unstructured":"Li, C., Chang, W., Cheng, Y., Yang, Y., P\u00f3czos, B.: MMD GAN: towards deeper understanding of moment matching network. CoRR arXiv:1705.08584"},{"key":"40_CR18","unstructured":"Li, Y., Swersky, K., Zemel, R.S.: Generative moment matching networks. In: ICML, pp. 1718\u20131727 (2015)"},{"key":"40_CR19","unstructured":"Liu, M., Tuzel, O.: Coupled generative adversarial networks. In: NIPS, pp. 469\u2013477 (2016)"},{"key":"40_CR20","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: ICCV, pp. 3730\u20133738 (2015)","DOI":"10.1109\/ICCV.2015.425"},{"key":"40_CR21","doi-asserted-by":"crossref","unstructured":"Mao, X., Li, Q., Xie, H., Lau, R.Y.K., Wang, Z.: Multi-class generative adversarial networks with the L2 loss function. CoRR arXiv:1611.04076 (2016)","DOI":"10.1109\/ICCV.2017.304"},{"key":"40_CR22","unstructured":"Mathieu, M., Couprie, C., LeCun, Y.: Deep multi-scale video prediction beyond mean square error. CoRR arXiv:1511.05440 (2015)"},{"key":"40_CR23","unstructured":"Mirza, M., Osindero, S.: Conditional generative adversarial nets. CoRR arXiv:1411.1784"},{"key":"40_CR24","unstructured":"Nowozin, S., Cseke, B., Tomioka, R.: f-GAN: training generative neural samplers using variational divergence minimization. In: NIPS, pp. 271\u2013279 (2016)"},{"key":"40_CR25","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. CoRR arXiv:1511.06434"},{"key":"40_CR26","unstructured":"Sutherland, D.J., et al.: Generative models and model criticism via optimized maximum mean discrepancy. CoRR arXiv:1611.04488"},{"key":"40_CR27","doi-asserted-by":"crossref","unstructured":"Vincent, P., Larochelle, H., Bengio, Y., Manzagol, P.: Extracting and composing robust features with denoising autoencoders. In: ICML, pp. 1096\u20131103 (2008)","DOI":"10.1145\/1390156.1390294"},{"issue":"4","key":"40_CR28","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"40_CR29","unstructured":"Wu, J., Zhang, C., Xue, T., Freeman, B., Tenenbaum, J.: Learning a probabilistic latent space of object shapes via 3D generative-adversarial modeling. In: NIPS, pp. 82\u201390 (2016)"},{"key":"40_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, H., et al.: StackGAN: text to photo-realistic image synthesis with stacked generative adversarial networks. CoRR abs\/1612.03242 (2016)","DOI":"10.1109\/ICCV.2017.629"},{"key":"40_CR31","unstructured":"Zhao, J.J., Mathieu, M., LeCun, Y.: Energy-based generative adversarial network. CoRR arXiv:1609.03126"},{"key":"40_CR32","unstructured":"Zhao, S., Song, J., Ermon, S.: InfoVAE: information maximizing variational autoencoders. CoRR arXiv:1706.02262"}],"container-title":["Lecture Notes in Computer Science","Advances in Multimedia Information Processing \u2013 PCM 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00767-6_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:28:42Z","timestamp":1709832522000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00767-6_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030007669","9783030007676"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00767-6_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"19 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PCM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim Conference on Multimedia","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hefei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pcm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/pcm2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}