{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T02:56:04Z","timestamp":1792810564462,"version":"4.5.0"},"publisher-location":"New York, NY, USA","reference-count":53,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"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 under Grant","award":["82090052"],"award-info":[{"award-number":["82090052"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"crossref"}]},{"name":"National Key R&D Program of China","award":["2021ZD0113502"],"award-info":[{"award-number":["2021ZD0113502"]}]},{"name":"Shanghai Municipal Science and Technology Major Project","award":["2021SHZDZX0103"],"award-info":[{"award-number":["2021SHZDZX0103"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3503161.3547755","type":"proceedings-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T11:43:01Z","timestamp":1665402181000},"page":"1708-1717","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":65,"title":["Learning Modality-Specific and -Agnostic Representations for Asynchronous Multimodal Language Sequences"],"prefix":"10.1145","author":[{"given":"Dingkang","family":"Yang","sequence":"first","affiliation":[{"name":"Academy for Engineering and Technology, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haopeng","family":"Kuang","sequence":"additional","affiliation":[{"name":"Academy for Engineering and Technology, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuai","family":"Huang","sequence":"additional","affiliation":[{"name":"Academy for Engineering and Technology, Fudan University &amp; Engineering Research Center of AI and Robotics, Ministry of Education &amp; Artifical Intelligence and Unmanned Systems Engineering Research Center of Jilin Province, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Academy for Engineering and Technology, Fudan University &amp; Jilin Provincial Key Laboratory of Intelligence Science and Engineering &amp; Ji Hua Laboratory, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,10,10]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text. arXiv preprint arXiv:2104.11178","author":"Akbari Hassan","year":"2021","unstructured":"Hassan Akbari , Linagzhe Yuan , Rui Qian , Wei-Hong Chuang , Shih-Fu Chang , Yin Cui , and Boqing Gong . 2021 . Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text. arXiv preprint arXiv:2104.11178 (2021). Hassan Akbari, Linagzhe Yuan, Rui Qian,Wei-Hong Chuang, Shih-Fu Chang, Yin Cui, and Boqing Gong. 2021. Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text. arXiv preprint arXiv:2104.11178 (2021)."},{"key":"e_1_3_2_2_2_1","volume-title":"Domain separation networks. Advances in neural information processing systems 29","author":"Bousmalis Konstantinos","year":"2016","unstructured":"Konstantinos Bousmalis , George Trigeorgis , Nathan Silberman , Dilip Krishnan , and Dumitru Erhan . 2016. Domain separation networks. Advances in neural information processing systems 29 ( 2016 ). Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, and Dumitru Erhan. 2016. Domain separation networks. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_2_2_3_1","volume-title":"IEMOCAP: Interactive emotional dyadic motion capture database. Language resources and evaluation 42, 4","author":"Busso Carlos","year":"2008","unstructured":"Carlos Busso , Murtaza Bulut , Chi-Chun Lee , Abe Kazemzadeh , Emily Mower , Samuel Kim , Jeannette N Chang , Sungbok Lee , and Shrikanth S Narayanan . 2008 . IEMOCAP: Interactive emotional dyadic motion capture database. Language resources and evaluation 42, 4 (2008), 335--359. Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, Emily Mower, Samuel Kim, Jeannette N Chang, Sungbok Lee, and Shrikanth S Narayanan. 2008. IEMOCAP: Interactive emotional dyadic motion capture database. Language resources and evaluation 42, 4 (2008), 335--359."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01472"},{"key":"e_1_3_2_2_5_1","volume-title":"COVAREP-A collaborative voice analysis repository for speech technologies. In 2014 ieee international conference on acoustics, speech and signal processing (icassp)","author":"Degottex Gilles","unstructured":"Gilles Degottex , John Kane , Thomas Drugman , Tuomo Raitio , and Stefan Scherer . 2014. COVAREP-A collaborative voice analysis repository for speech technologies. In 2014 ieee international conference on acoustics, speech and signal processing (icassp) . IEEE , 960--964. Gilles Degottex, John Kane, Thomas Drugman, Tuomo Raitio, and Stefan Scherer. 2014. COVAREP-A collaborative voice analysis repository for speech technologies. In 2014 ieee international conference on acoustics, speech and signal processing (icassp). IEEE, 960--964."},{"key":"e_1_3_2_2_6_1","volume-title":"Proceedings of the 28th ACM International Conference on Multimedia","volume":"34","author":"Devamanyu Hazarika","year":"2020","unstructured":"Hazarika Devamanyu , Zimmermann Roger , and Poria Soujanya . 2020 . MISA: Modality-invariant and-specific representations for multimodal sentiment analysis .. In Proceedings of the 28th ACM International Conference on Multimedia , Vol. 34 . 1122--1131. Hazarika Devamanyu, Zimmermann Roger, and Poria Soujanya. 2020. MISA: Modality-invariant and-specific representations for multimodal sentiment analysis.. In Proceedings of the 28th ACM International Conference on Multimedia, Vol. 34. 1122--1131."},{"key":"e_1_3_2_2_7_1","volume-title":"Multi-modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network. In International Workshop on Machine Learning in Clinical Neuroimaging. Springer, 82--91","author":"Duan Wenting","year":"2021","unstructured":"Wenting Duan , Lei Zhang , Jordan Colman , Giosue Gulli , and Xujiong Ye . 2021 . Multi-modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network. In International Workshop on Machine Learning in Clinical Neuroimaging. Springer, 82--91 . Wenting Duan, Lei Zhang, Jordan Colman, Giosue Gulli, and Xujiong Ye. 2021. Multi-modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network. In International Workshop on Machine Learning in Clinical Neuroimaging. Springer, 82--91."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.547"},{"key":"e_1_3_2_2_9_1","volume-title":"International conference on machine learning. PMLR, 1180-- 1189","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor Lempitsky . 2015 . Unsupervised domain adaptation by backpropagation . In International conference on machine learning. PMLR, 1180-- 1189 . Yaroslav Ganin and Victor Lempitsky. 2015. Unsupervised domain adaptation by backpropagation. In International conference on machine learning. PMLR, 1180-- 1189."},{"key":"e_1_3_2_2_10_1","volume-title":"Generative adversarial nets. Advances in neural information processing systems 27","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow , Jean Pouget-Abadie , Mehdi Mirza , Bing Xu , David Warde-Farley , Sherjil Ozair , Aaron Courville , and Yoshua Bengio . 2014. Generative adversarial nets. Advances in neural information processing systems 27 ( 2014 ). Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative adversarial nets. Advances in neural information processing systems 27 (2014)."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143891"},{"key":"e_1_3_2_2_12_1","unstructured":"P. Hai T. Manzini P. P. Liang and Barnab\u00e1s Pocz\u00f3s. 2018. Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis. (2018).  P. Hai T. Manzini P. P. Liang and Barnab\u00e1s Pocz\u00f3s. 2018. Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis. (2018)."},{"key":"e_1_3_2_2_13_1","volume-title":"Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412","author":"Han Wei","year":"2021","unstructured":"Wei Han , Hui Chen , and Soujanya Poria . 2021. Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412 ( 2021 ). Wei Han, Hui Chen, and Soujanya Poria. 2021. Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis. arXiv preprint arXiv:2109.00412 (2021)."},{"key":"e_1_3_2_2_14_1","volume-title":"Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415","author":"Hendrycks Dan","year":"2016","unstructured":"Dan Hendrycks and Kevin Gimpel . 2016. Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415 ( 2016 ). Dan Hendrycks and Kevin Gimpel. 2016. Gaussian error linear units (gelus). arXiv preprint arXiv:1606.08415 (2016)."},{"key":"e_1_3_2_2_15_1","volume-title":"Long short-term memory. Neural computation 9, 8","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber . 1997. Long short-term memory. Neural computation 9, 8 ( 1997 ), 1735--1780. Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation 9, 8 (1997), 1735--1780."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2749576"},{"key":"e_1_3_2_2_17_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence 36","author":"Huang Hao","year":"2022","unstructured":"Hao Huang , Yongtao Wang , Zhaoyu Chen , Yuze Zhang , Yuheng Li , Zhi Tang , Wei Chu , Jingdong Chen , Weisi Lin , and Kai-Kuang Ma . 2022 . Carnegie Mellon UniversityA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes . Proceedings of the AAAI Conference on Artificial Intelligence 36 , 1 (Jun. 2022), 989--997. https:\/\/doi.org\/10.1609\/aaai.v36i1.19982 Hao Huang, Yongtao Wang, Zhaoyu Chen, Yuze Zhang, Yuheng Li, Zhi Tang, Wei Chu, Jingdong Chen,Weisi Lin, and Kai-Kuang Ma. 2022. Carnegie Mellon UniversityA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes. Proceedings of the AAAI Conference on Artificial Intelligence 36, 1 (Jun. 2022), 989--997. https:\/\/doi.org\/10.1609\/aaai.v36i1.19982"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00403"},{"key":"e_1_3_2_2_19_1","unstructured":"iMotions. 2017. Facial expression analysis.  iMotions. 2017. Facial expression analysis."},{"key":"e_1_3_2_2_20_1","volume-title":"Attention is not explanation. arXiv preprint arXiv:1902.10186","author":"Jain Sarthak","year":"2019","unstructured":"Sarthak Jain and Byron C Wallace . 2019. Attention is not explanation. arXiv preprint arXiv:1902.10186 ( 2019 ). Sarthak Jain and Byron C Wallace. 2019. Attention is not explanation. arXiv preprint arXiv:1902.10186 (2019)."},{"key":"e_1_3_2_2_21_1","volume-title":"MATLAB deep learning","author":"Kim Phil","unstructured":"Phil Kim . 2017. Convolutional neural network . In MATLAB deep learning . Springer , 121--147. Phil Kim. 2017. Convolutional neural network. In MATLAB deep learning. Springer, 121--147."},{"key":"e_1_3_2_2_22_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.01024"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380163"},{"key":"e_1_3_2_2_25_1","volume-title":"Multimodal language analysis with recurrent multistage fusion. arXiv preprint arXiv:1808.03920","author":"Liang Paul Pu","year":"2018","unstructured":"Paul Pu Liang , Ziyin Liu , Amir Zadeh , and Louis-Philippe Morency . 2018. Multimodal language analysis with recurrent multistage fusion. arXiv preprint arXiv:1808.03920 ( 2018 ). Paul Pu Liang, Ziyin Liu, Amir Zadeh, and Louis-Philippe Morency. 2018. Multimodal language analysis with recurrent multistage fusion. arXiv preprint arXiv:1808.03920 (2018)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00804"},{"key":"e_1_3_2_2_27_1","volume-title":"Efficient Universal Shuffle Attack for Visual Object Tracking. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2739--2743","author":"Liu Siao","year":"2022","unstructured":"Siao Liu , Zhaoyu Chen , Wei Li , Jiwei Zhu , Jiafeng Wang , Wenqiang Zhang , and Zhongxue Gan . 2022 . Efficient Universal Shuffle Attack for Visual Object Tracking. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2739--2743 . https:\/\/doi.org\/10.1109\/ICASSP43922. 2022.9747773 Siao Liu, Zhaoyu Chen, Wei Li, Jiwei Zhu, Jiafeng Wang, Wenqiang Zhang, and Zhongxue Gan. 2022. Efficient Universal Shuffle Attack for Visual Object Tracking. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2739--2743. https:\/\/doi.org\/10.1109\/ICASSP43922. 2022.9747773"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2022.3161061"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"Yang Liu Jing Liu Xiaoguang Zhu Donglai Wei Xiaohong Huang and Liang Song. 2022. Learning Task-Specific Representation for Video Anomaly Detection with Spatial-Temporal Attention. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP). 2190--2194. https:\/\/doi.org\/10.1109\/ICASSP43922.2022.9746822  Yang Liu Jing Liu Xiaoguang Zhu Donglai Wei Xiaohong Huang and Liang Song. 2022. Learning Task-Specific Representation for Video Anomaly Detection with Spatial-Temporal Attention. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP). 2190--2194. https:\/\/doi.org\/10.1109\/ICASSP43922.2022.9746822","DOI":"10.1109\/ICASSP43922.2022.9746822"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00258"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2018.06.005"},{"key":"e_1_3_2_2_32_1","volume-title":"Deep spatio-temporal features for multimodal emotion recognition. In 2017 IEEE winter conference on applications of computer vision (WACV)","author":"Nguyen Dung","unstructured":"Dung Nguyen , Kien Nguyen , Sridha Sridharan , Afsane Ghasemi , David Dean , and Clinton Fookes . 2017. Deep spatio-temporal features for multimodal emotion recognition. In 2017 IEEE winter conference on applications of computer vision (WACV) . IEEE , 1215--1223. Dung Nguyen, Kien Nguyen, Sridha Sridharan, Afsane Ghasemi, David Dean, and Clinton Fookes. 2017. Deep spatio-temporal features for multimodal emotion recognition. In 2017 IEEE winter conference on applications of computer vision (WACV). IEEE, 1215--1223."},{"key":"e_1_3_2_2_33_1","unstructured":"G. Park and W. Im. 2016. Image-Text Multi-Modal Representation Learning by Adversarial Backpropagation. (2016).  G. Park and W. Im. 2016. Image-Text Multi-Modal Representation Learning by Adversarial Backpropagation. (2016)."},{"key":"e_1_3_2_2_34_1","volume-title":"Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke , Sam Gross , Francisco Massa , Adam Lerer , James Bradbury , Gregory Chanan , Trevor Killeen , Zeming Lin , Natalia Gimelshein , Luca Antiga , 2019 . Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019). Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019. Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33016892"},{"key":"e_1_3_2_2_37_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence 34","author":"Sun Z.","year":"2020","unstructured":"Z. Sun , P. Sarma , W. Sethares , and Y. Liang . 2020. Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis . Proceedings of the AAAI Conference on Artificial Intelligence 34 , 5 ( 2020 ), 8992--8999. Z. Sun, P. Sarma,W. Sethares, and Y. Liang. 2020. Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis. Proceedings of the AAAI Conference on Artificial Intelligence 34, 5 (2020), 8992--8999."},{"key":"e_1_3_2_2_38_1","volume-title":"Proceedings of the conference. Association for Computational Linguistics. Meeting","volume":"2019","author":"Hubert Tsai Yao-Hung","year":"2019","unstructured":"Yao-Hung Hubert Tsai , Shaojie Bai , Paul Pu Liang , J Zico Kolter , Louis-Philippe Morency , and Ruslan Salakhutdinov . 2019 . Multimodal transformer for unaligned multimodal language sequences . In Proceedings of the conference. Association for Computational Linguistics. Meeting , Vol. 2019 . NIH Public Access, 6558. Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J Zico Kolter, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2019. Multimodal transformer for unaligned multimodal language sequences. In Proceedings of the conference. Association for Computational Linguistics. Meeting, Vol. 2019. NIH Public Access, 6558."},{"key":"e_1_3_2_2_39_1","volume-title":"Amir Zadeh, Louis-Philippe Morency, and Ruslan Salakhutdinov.","author":"Hubert Tsai Yao-Hung","year":"2018","unstructured":"Yao-Hung Hubert Tsai , Paul Pu Liang , Amir Zadeh, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2018 . Learning factorized multimodal representations. arXiv preprint arXiv:1806.06176 (2018). Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2018. Learning factorized multimodal representations. arXiv preprint arXiv:1806.06176 (2018)."},{"key":"e_1_3_2_2_40_1","volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing","volume":"2020","author":"Hubert Tsai Yao-Hung","year":"2020","unstructured":"Yao-Hung Hubert Tsai , Martin Q Ma , Muqiao Yang , Ruslan Salakhutdinov , and Louis-Philippe Morency . 2020 . Multimodal routing: Improving local and global interpretability of multimodal language analysis . In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing , Vol. 2020 . NIH Public Access , 1823. Yao-Hung Hubert Tsai, Martin Q Ma, Muqiao Yang, Ruslan Salakhutdinov, and Louis-Philippe Morency. 2020. Multimodal routing: Improving local and global interpretability of multimodal language analysis. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing, Vol. 2020. NIH Public Access, 1823."},{"key":"e_1_3_2_2_41_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008.  Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475438"},{"key":"e_1_3_2_2_43_1","volume-title":"Deep variational canonical correlation analysis. arXiv preprint arXiv:1610.03454","author":"Wang Weiran","year":"2016","unstructured":"Weiran Wang , Xinchen Yan , Honglak Lee , and Karen Livescu . 2016. Deep variational canonical correlation analysis. arXiv preprint arXiv:1610.03454 ( 2016 ). Weiran Wang, Xinchen Yan, Honglak Lee, and Karen Livescu. 2016. Deep variational canonical correlation analysis. arXiv preprint arXiv:1610.03454 (2016)."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33017216"},{"key":"e_1_3_2_2_45_1","unstructured":"Yujing Wang Yaming Yang Jiangang Bai Mingliang Zhang Jing Bai Jing Yu Ce Zhang and Yunhai Tong. 2020. Predictive Attention Transformer: Improving Transformer with Attention Map Prediction. (2020).  Yujing Wang Yaming Yang Jiangang Bai Mingliang Zhang Jing Bai Jing Yu Ce Zhang and Yunhai Tong. 2020. Predictive Attention Transformer: Improving Transformer with Attention Map Prediction. (2020)."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.417"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1208"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2016.94"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.77"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"crossref","unstructured":"Peng Zhai Jie Luo Zhiyan Dong Lihua Zhang ShunliWang and Dingkang Yang. 2022. Robust Adversarial Reinforcement Learning with Dissipation Inequation Constraint. (2022).  Peng Zhai Jie Luo Zhiyan Dong Lihua Zhang ShunliWang and Dingkang Yang. 2022. Robust Adversarial Reinforcement Learning with Dissipation Inequation Constraint. (2022).","DOI":"10.1609\/aaai.v36i5.20481"},{"key":"e_1_3_2_2_51_1","volume-title":"Trends and Challenges. In 2019 International Conference on Machine Learning and Cybernetics (ICMLC).","author":"Zhang S. F.","unstructured":"S. F. Zhang , J. H. Zhai , B. J. Xie , Y. Zhan , and X. Wang . 2019. Multimodal Representation Learning: Advances , Trends and Challenges. In 2019 International Conference on Machine Learning and Cybernetics (ICMLC). S. F. Zhang, J. H. Zhai, B. J. Xie, Y. Zhan, and X. Wang. 2019. Multimodal Representation Learning: Advances, Trends and Challenges. In 2019 International Conference on Machine Learning and Cybernetics (ICMLC)."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"crossref","unstructured":"Y. Zhang M. Chen J. Shen and C. Wang. 2022. Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition. arXiv e-prints (2022).  Y. Zhang M. Chen J. Shen and C. Wang. 2022. Tailor Versatile Multi-modal Learning for Multi-label Emotion Recognition. arXiv e-prints (2022).","DOI":"10.1609\/aaai.v36i8.20895"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.374"}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 30th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3547755","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3503161.3547755","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T15:30:40Z","timestamp":1750174240000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3547755"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":53,"alternative-id":["10.1145\/3503161.3547755","10.1145\/3503161"],"URL":"https:\/\/doi.org\/10.1145\/3503161.3547755","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}