{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T23:53:13Z","timestamp":1786233193948,"version":"build-2736575974"},"publisher-location":"New York, NY, USA","reference-count":49,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,10,15]],"date-time":"2019-10-15T00:00:00Z","timestamp":1571097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Natural Science Foundation of China (NSFC)","award":["61772111"],"award-info":[{"award-number":["61772111"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,10,15]]},"DOI":"10.1145\/3343031.3351053","type":"proceedings-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T16:32:26Z","timestamp":1571675546000},"page":"1712-1720","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":31,"title":["Learning Disentangled Representation for Cross-Modal Retrieval with Deep Mutual Information Estimation"],"prefix":"10.1145","author":[{"given":"Weikuo","family":"Guo","sequence":"first","affiliation":[{"name":"Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaibo","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences & CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangwei","family":"Kong","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"He","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences & CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,10,15]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mohamed Ishmael Belghazi Aristide Baratin Sai Rajeshwar Sherjil Ozair Yoshua Bengio Devon Hjelm and Aaron Courville. 2018. Mutual Information Neural Estimation. In ICML. 530--539.  Mohamed Ishmael Belghazi Aristide Baratin Sai Rajeshwar Sherjil Ozair Yoshua Bengio Devon Hjelm and Aaron Courville. 2018. Mutual Information Neural Estimation. In ICML. 530--539."},{"key":"e_1_3_2_1_2_1","volume-title":"An information-maximization approach to blind separation and blind deconvolution. Neural computation","author":"Bell Anthony J","year":"1995"},{"key":"e_1_3_2_1_3_1","volume-title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets. In NIPS. 2172--2180.","author":"Chen Xi","year":"2016"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.3160360204"},{"key":"e_1_3_2_1_5_1","unstructured":"Emilien Dupont. 2018. Learning disentangled joint continuous and discrete representations. In NIPS .  Emilien Dupont. 2018. Learning disentangled joint continuous and discrete representations. In NIPS ."},{"key":"e_1_3_2_1_6_1","unstructured":"Venice Erin Liong Jiwen Lu Yap-Peng Tan and Jie Zhou. 2017. Cross-Modal Deep Variational Hashing. In ICCV. 4097--4105.  Venice Erin Liong Jiwen Lu Yap-Peng Tan and Jie Zhou. 2017. Cross-Modal Deep Variational Hashing. In ICCV. 4097--4105."},{"key":"e_1_3_2_1_7_1","volume-title":"Jamie Ryan Kiros, and Sanja Fidler","author":"Faghri Fartash","year":"2017"},{"key":"e_1_3_2_1_8_1","volume-title":"Improving visual-semantic embeddings with hard negatives. arXiv preprint arXiv:1707.05612","year":"2017"},{"key":"e_1_3_2_1_9_1","unstructured":"Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In ICML. 1180--1189.  Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In ICML. 1180--1189."},{"key":"e_1_3_2_1_10_1","unstructured":"Abel Gonzalez-Garcia Joost van de Weijer and Yoshua Bengio. 2018. Image-to-image translation for cross-domain disentanglement. In NIPS . 710--720.  Abel Gonzalez-Garcia Joost van de Weijer and Yoshua Bengio. 2018. Image-to-image translation for cross-domain disentanglement. In NIPS . 710--720."},{"key":"e_1_3_2_1_11_1","unstructured":"Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS. 2672--2680.  Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NIPS. 2672--2680."},{"key":"e_1_3_2_1_12_1","unstructured":"Jiuxiang Gu Jianfei Cai Shafiq R Joty Li Niu and Gang Wang. 2018. Look imagine and match: Improving textual-visual cross-modal retrieval with generative models. In CVPR. 7181--7189.  Jiuxiang Gu Jianfei Cai Shafiq R Joty Li Niu and Gang Wang. 2018. Look imagine and match: Improving textual-visual cross-modal retrieval with generative models. In CVPR. 7181--7189."},{"key":"e_1_3_2_1_13_1","unstructured":"Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In NIPS. 5767--5777.  Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In NIPS. 5767--5777."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Weikuo Guo Liang Jian Kong Xiangwei Song Lingxiao and He Ran. 2018. X-GACMN: An X-Shaped Generative Adversarial Cross-Modal Network with Hypersphere Embedding. In ACCV. 513--529.  Weikuo Guo Liang Jian Kong Xiangwei Song Lingxiao and He Ran. 2018. X-GACMN: An X-Shaped Generative Adversarial Cross-Modal Network with Hypersphere Embedding. In ACCV. 513--529.","DOI":"10.1007\/978-3-030-20873-8_33"},{"key":"e_1_3_2_1_15_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778.  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778."},{"key":"e_1_3_2_1_16_1","first-page":"6","article-title":"beta-vae: Learning basic visual concepts with a constrained variational framework","volume":"2","author":"Higgins Irina","year":"2017","journal-title":"ICLR"},{"key":"e_1_3_2_1_17_1","unstructured":"R Devon Hjelm Alex Fedorov Samuel Lavoie-Marchildon Karan Grewal Adam Trischler and Yoshua Bengio. 2019. Learning deep representations by mutual information estimation and maximization. In ICLR .  R Devon Hjelm Alex Fedorov Samuel Lavoie-Marchildon Karan Grewal Adam Trischler and Yoshua Bengio. 2019. Learning deep representations by mutual information estimation and maximization. In ICLR ."},{"key":"e_1_3_2_1_18_1","unstructured":"Ronghang Hu Jacob Andreas Marcus Rohrbach Trevor Darrell and Kate Saenko. 2017. Learning to Reason: End-To-End Module Networks for Visual Question Answering. In ICCV . 804--813.  Ronghang Hu Jacob Andreas Marcus Rohrbach Trevor Darrell and Kate Saenko. 2017. Learning to Reason: End-To-End Module Networks for Visual Question Answering. In ICCV . 804--813."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Yan Huang Wei Wang and Liang Wang. 2017. Instance-aware image and sentence matching with selective multimodal lstm. In CVPR . 2310--2318.  Yan Huang Wei Wang and Liang Wang. 2017. Instance-aware image and sentence matching with selective multimodal lstm. In CVPR . 2310--2318.","DOI":"10.1109\/CVPR.2017.767"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Qing-Yuan Jiang and Wu-Jun Li. 2017. Deep Cross-Modal Hashing. In CVPR. 3232--3240.  Qing-Yuan Jiang and Wu-Jun Li. 2017. Deep Cross-Modal Hashing. In CVPR. 3232--3240.","DOI":"10.1109\/CVPR.2017.348"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Andrej Karpathy and Li Fei-Fei. 2015. Deep visual-semantic alignments for generating image descriptions. In CVPR . 3128--3137.  Andrej Karpathy and Li Fei-Fei. 2015. Deep visual-semantic alignments for generating image descriptions. In CVPR . 3128--3137.","DOI":"10.1109\/CVPR.2015.7298932"},{"key":"e_1_3_2_1_22_1","volume-title":"Disentangling by factorising. arXiv preprint arXiv:1802.05983","author":"Kim Hyunjik","year":"2018"},{"key":"e_1_3_2_1_23_1","volume-title":"Adam: A method for stochastic optimization. In ICLR .","author":"Kingma Diederik P","year":"2015"},{"key":"e_1_3_2_1_24_1","unstructured":"Diederik P Kingma and Max Welling. 2014. Auto-encoding variational bayes. In ICLR .  Diederik P Kingma and Max Welling. 2014. Auto-encoding variational bayes. In ICLR ."},{"key":"e_1_3_2_1_25_1","volume-title":"Unifying visual-semantic embeddings with multimodal neural language models. arXiv preprint arXiv:1411.2539","author":"Kiros Ryan","year":"2014"},{"key":"e_1_3_2_1_26_1","unstructured":"Hsin-Ying Lee Hung-Yu Tseng Jia-Bin Huang Maneesh Singh and Ming-Hsuan Yang. 2018. Diverse Image-to-Image Translation via Disentangled Representations. In ECCV . 35--51.  Hsin-Ying Lee Hung-Yu Tseng Jia-Bin Huang Maneesh Singh and Ming-Hsuan Yang. 2018. Diverse Image-to-Image Translation via Disentangled Representations. In ECCV . 35--51."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Lizhao Li Guoyong Cai and Nannan Chen. 2018. A Rumor Events Detection Method Based on Deep Bidirectional GRU Neural Network. In ICIVC . 755--759.  Lizhao Li Guoyong Cai and Nannan Chen. 2018. A Rumor Events Detection Method Based on Deep Bidirectional GRU Neural Network. In ICIVC . 755--759.","DOI":"10.1109\/ICIVC.2018.8492819"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Tsung-Yi Lin Michael Maire Serge Belongie James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1r and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In ECCV. 740--755.  Tsung-Yi Lin Michael Maire Serge Belongie James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1r and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In ECCV. 740--755.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/2.36"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Yang Liu Zhaowen Wang Hailin Jin and Ian Wassell. 2018. Multi-Task Adversarial Network for Disentangled Feature Learning. In CVPR . 3743--3751.  Yang Liu Zhaowen Wang Hailin Jin and Ian Wassell. 2018. Multi-Task Adversarial Network for Disentangled Feature Learning. In CVPR . 3743--3751.","DOI":"10.1109\/CVPR.2018.00394"},{"key":"e_1_3_2_1_31_1","unstructured":"Boyu Lu Jun-Cheng Chen and Rama Chellappa. 2019. Unsupervised Domain-Specific Deblurring via Disentangled Representations. In CVPR . 10225--10234.  Boyu Lu Jun-Cheng Chen and Rama Chellappa. 2019. Unsupervised Domain-Specific Deblurring via Disentangled Representations. In CVPR . 10225--10234."},{"key":"e_1_3_2_1_32_1","volume-title":"The CM Algorithm for the Maximum Mutual Information Classifications of Unseen Instances. arXiv preprint arXiv:1901.09902","author":"Chenguang Lu.","year":"2019"},{"key":"e_1_3_2_1_33_1","unstructured":"Jiasen Lu Caiming Xiong Devi Parikh and Richard Socher. 2017. Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning. In CVPR . 375--383.  Jiasen Lu Caiming Xiong Devi Parikh and Richard Socher. 2017. Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning. In CVPR . 375--383."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Lin Ma Zhengdong Lu Lifeng Shang and Hang Li. 2015. Multimodal convolutional neural networks for matching image and sentence. In ICCV . 2623--2631.  Lin Ma Zhengdong Lu Lifeng Shang and Hang Li. 2015. Multimodal convolutional neural networks for matching image and sentence. In ICCV . 2623--2631.","DOI":"10.1109\/ICCV.2015.301"},{"key":"e_1_3_2_1_35_1","unstructured":"Ofir Nachum Shixiang Gu Honglak Lee and Sergey Levine. 2019. Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. In ICLR .  Ofir Nachum Shixiang Gu Honglak Lee and Sergey Levine. 2019. Near-Optimal Representation Learning for Hierarchical Reinforcement Learning. In ICLR ."},{"key":"e_1_3_2_1_36_1","unstructured":"Hyeonseob Nam Jung-Woo Ha and Jeonghee Kim. 2017. Dual attention networks for multimodal reasoning and matching. In CVPR . 299--307.  Hyeonseob Nam Jung-Woo Ha and Jeonghee Kim. 2017. Dual attention networks for multimodal reasoning and matching. In CVPR . 299--307."},{"key":"e_1_3_2_1_37_1","unstructured":"Zhenxing Niu Mo Zhou Le Wang Xinbo Gao and Gang Hua. 2017. Hierarchical multimodal lstm for dense visual-semantic embedding. In ICCV . 1881--1889.  Zhenxing Niu Mo Zhou Le Wang Xinbo Gao and Gang Hua. 2017. Hierarchical multimodal lstm for dense visual-semantic embedding. In ICCV . 1881--1889."},{"key":"e_1_3_2_1_38_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. In ICLR .  Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. In ICLR ."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Luan Tran Xi Yin and Xiaoming Liu. 2017. Disentangled Representation Learning GAN for Pose-Invariant Face Recognition. In CVPR . 1415--1424.  Luan Tran Xi Yin and Xiaoming Liu. 2017. Disentangled Representation Learning GAN for Pose-Invariant Face Recognition. In CVPR . 1415--1424.","DOI":"10.1109\/CVPR.2017.141"},{"key":"e_1_3_2_1_40_1","unstructured":"Ivan Vendrov Ryan Kiros Sanja Fidler and Raquel Urtasun. 2016. Order-embeddings of images and language. In ICLR .  Ivan Vendrov Ryan Kiros Sanja Fidler and Raquel Urtasun. 2016. Order-embeddings of images and language. In ICLR ."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Bokun Wang Yang Yang Xing Xu Alan Hanjalic and Heng Tao Shen. 2017. Adversarial Cross-Modal Retrieval. In ACM MM. 154--162.  Bokun Wang Yang Yang Xing Xu Alan Hanjalic and Heng Tao Shen. 2017. Adversarial Cross-Modal Retrieval. In ACM MM. 154--162.","DOI":"10.1145\/3123266.3123326"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2797921"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Liwei Wang Yin Li and Svetlana Lazebnik. 2016. Learning deep structure-preserving image-text embeddings. In CVPR . 5005--5013.  Liwei Wang Yin Li and Svetlana Lazebnik. 2016. Learning deep structure-preserving image-text embeddings. In CVPR . 5005--5013.","DOI":"10.1109\/CVPR.2016.541"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Shuohang Wang Sheng Zhang Yelong Shen Xiaodong Liu Jingjing Liu Jianfeng Gao and Jing Jiang. 2019. Unsupervised Deep Structured Semantic Models for Commonsense Reasoning. In NAACL . 882--891.  Shuohang Wang Sheng Zhang Yelong Shen Xiaodong Liu Jingjing Liu Jianfeng Gao and Jing Jiang. 2019. Unsupervised Deep Structured Semantic Models for Commonsense Reasoning. In NAACL . 882--891.","DOI":"10.18653\/v1\/N19-1094"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00166"},{"key":"e_1_3_2_1_46_1","first-page":"1276","article-title":"Adaptive Semi-supervised Feature Selection for Cross-modal Retrieval","volume":"21","author":"Yu En","year":"2018","journal-title":"IEEE TMM"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Yibing Zhan Jun Yu Zhou Yu Rong Zhang Dacheng Tao and Qi Tian. 2018. Comprehensive Distance-Preserving Autoencoders for Cross-Modal Retrieval. In ACM MM . 1137--1145.  Yibing Zhan Jun Yu Zhou Yu Rong Zhang Dacheng Tao and Qi Tian. 2018. Comprehensive Distance-Preserving Autoencoders for Cross-Modal Retrieval. In ACM MM . 1137--1145.","DOI":"10.1145\/3240508.3240607"},{"key":"e_1_3_2_1_48_1","volume-title":"High-Resolution Talking Face Generation via Mutual Information Approximation. arXiv preprint arXiv:1812.06589","author":"Zhu Hao","year":"2018"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2805286"}],"event":{"name":"MM '19: The 27th ACM International Conference on Multimedia","location":"Nice France","acronym":"MM '19","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 27th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3351053","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3343031.3351053","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:12Z","timestamp":1750201992000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3351053"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,15]]},"references-count":49,"alternative-id":["10.1145\/3343031.3351053","10.1145\/3343031"],"URL":"https:\/\/doi.org\/10.1145\/3343031.3351053","relation":{},"subject":[],"published":{"date-parts":[[2019,10,15]]},"assertion":[{"value":"2019-10-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}