{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T22:20:13Z","timestamp":1776291613540,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":11,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,7,15]],"date-time":"2018-07-15T00:00:00Z","timestamp":1531612800000},"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":[[2018,7,15]]},"DOI":"10.1145\/3230519.3230598","type":"proceedings-article","created":{"date-parts":[[2018,7,11]],"date-time":"2018-07-11T20:16:07Z","timestamp":1531340167000},"page":"71-74","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Food image generation using a large amount of food images with conditional GAN"],"prefix":"10.1145","author":[{"given":"Yoshifumi","family":"Ito","sequence":"first","affiliation":[{"name":"The University of Electro-Communications, Tokyo"}]},{"given":"Wataru","family":"Shimoda","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications, Tokyo"}]},{"given":"Keiji","family":"Yanai","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications, Tokyo"}]}],"member":"320","published-online":{"date-parts":[[2018,7,15]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"2672","author":"Goodfellow I.","year":"2014","unstructured":"I. Goodfellow , J. Pouget-Abadie , M. Mirza , B. Xu , D. Warde-Farley , S. Ozair , A. Courville and Y. Bengio , Generative Adversarial Nets, Advances in Neural Information Processing Systems , pp. 2672 -- 2680 , 2014 . I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville and Y. Bengio, Generative Adversarial Nets, Advances in Neural Information Processing Systems, pp. 2672--2680, 2014.","journal-title":"Generative Adversarial Nets, Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_2_1","volume-title":"Conditional Generative Adversarial Nets, arXiv:1411.1784","author":"Mirza M.","year":"2014","unstructured":"M. Mirza and S. Osindero , Conditional Generative Adversarial Nets, arXiv:1411.1784 , 2014 . M. Mirza and S. Osindero, Conditional Generative Adversarial Nets, arXiv:1411.1784, 2014."},{"key":"e_1_3_2_1_3_1","volume-title":"Advances in Neural Information Processing Systems, 1486--1494","author":"Denton E.","year":"2015","unstructured":"E. Denton , S. Chintala , A. Szlam and R. Fergus , Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , Advances in Neural Information Processing Systems, 1486--1494 , 2015 . E. Denton, S. Chintala, A. Szlam and R. Fergus, Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks, Advances in Neural Information Processing Systems, 1486--1494, 2015."},{"key":"e_1_3_2_1_4_1","volume-title":"Proc. of International Conference on Learning Representations","author":"Radford A.","year":"2016","unstructured":"A. Radford , L. Metz and S. Chintala , Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , Proc. of International Conference on Learning Representations , 2016 . A. Radford, L. Metz and S. Chintala, Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, Proc. of International Conference on Learning Representations, 2016."},{"key":"e_1_3_2_1_5_1","volume-title":"Advances in Neural Information Processing Systems, 271--279","author":"Nowozin S.","year":"2016","unstructured":"S. Nowozin , B. Cseke and R. Tomioka , f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization , Advances in Neural Information Processing Systems, 271--279 , 2016 . S. Nowozin, B. Cseke and R. Tomioka, f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization, Advances in Neural Information Processing Systems, 271--279, 2016."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"e_1_3_2_1_7_1","volume-title":"Wassersstein GAN, arXiv:1701.07875","author":"Arjovsky M.","year":"2017","unstructured":"M. Arjovsky , S. Chintala and L. Bottou , Wassersstein GAN, arXiv:1701.07875 , 2017 . M. Arjovsky, S. Chintala and L. Bottou, Wassersstein GAN, arXiv:1701.07875, 2017."},{"key":"e_1_3_2_1_8_1","volume-title":"Advances in Neural Information Processing Systems, 2769--5779","author":"Gulrajani I.","year":"2017","unstructured":"I. Gulrajani , F. Ahmed , M. Arjovsky , V. Dumoulin and A. C. Courville , Improved Training of Wasserstein GANs , Advances in Neural Information Processing Systems, 2769--5779 , 2017 . I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin and A. C. Courville, Improved Training of Wasserstein GANs, Advances in Neural Information Processing Systems, 2769--5779, 2017."},{"key":"e_1_3_2_1_9_1","volume-title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation, arXiv:1710.10196","author":"Karras T.","year":"2017","unstructured":"T. Karras , S. Laine and J. Lehtinen , Progressive Growing of GANs for Improved Quality, Stability, and Variation, arXiv:1710.10196 , 2017 . T. Karras, S. Laine and J. Lehtinen, Progressive Growing of GANs for Improved Quality, Stability, and Variation, arXiv:1710.10196, 2017."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2012.157"},{"key":"e_1_3_2_1_11_1","volume-title":"Advances in Neural Information Processing Systems, 2234--2242","author":"Salimans T.","year":"2016","unstructured":"T. Salimans , I. Goodfellow , W. Zaremba , V. Cheung , A. Radford and X. Chen , Improved Techniques for Training GANs , Advances in Neural Information Processing Systems, 2234--2242 , 2016 . T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford and X. Chen, Improved Techniques for Training GANs, Advances in Neural Information Processing Systems, 2234--2242, 2016."}],"event":{"name":"CEA\/MADiMa2018: Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary Management in conjunction with the 27th International Joint Conference on Artificial Intelligence IJCAI","location":"Stockholm Sweden","acronym":"CEA\/MADiMa2018"},"container-title":["Proceedings of the Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3230519.3230598","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3230519.3230598","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:39:23Z","timestamp":1750210763000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3230519.3230598"}},"subtitle":["ramenGAN and recipeGAN"],"short-title":[],"issued":{"date-parts":[[2018,7,15]]},"references-count":11,"alternative-id":["10.1145\/3230519.3230598","10.1145\/3230519"],"URL":"https:\/\/doi.org\/10.1145\/3230519.3230598","relation":{},"subject":[],"published":{"date-parts":[[2018,7,15]]},"assertion":[{"value":"2018-07-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}