{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T02:50:51Z","timestamp":1761101451852,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key Research and Development Program","award":["2018AAA0101503"],"award-info":[{"award-number":["2018AAA0101503"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2018C01004"],"award-info":[{"award-number":["2018C01004"]}]},{"name":"National Natural Science Foundation of China","award":["61976186"],"award-info":[{"award-number":["61976186"]}]},{"name":"the Major Scientifc Research Project of Zhejiang Lab","award":["2019KD0AC01"],"award-info":[{"award-number":["2019KD0AC01"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413955","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T12:26:18Z","timestamp":1602505578000},"page":"2842-2851","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Unsupervised Learning Facial Parameter Regressor for Action Unit Intensity Estimation via Differentiable Renderer"],"prefix":"10.1145","author":[{"given":"Xinhui","family":"Song","sequence":"first","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]},{"given":"Tianyang","family":"Shi","sequence":"additional","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]},{"given":"Zunlei","family":"Feng","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"given":"Mingli","family":"Song","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"given":"Jackie","family":"Lin","sequence":"additional","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]},{"given":"Chuanjie","family":"Lin","sequence":"additional","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]},{"given":"Changjie","family":"Fan","sequence":"additional","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]},{"given":"Yi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Netease Fuxi AI Lab, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Automatic Face and Gesture Recognition","volume":"6","author":"Tadas Baltruvs","year":"2015","unstructured":"Tadas Baltruvs aitis, Marwa Mahmoud , and Peter Robinson . 2015 . Cross-dataset learning and person-specific normalisation for automatic action unit detection . In Automatic Face and Gesture Recognition , Vol. 6 . IEEE, 1--6. Tadas Baltruvs aitis, Marwa Mahmoud, and Peter Robinson. 2015. Cross-dataset learning and person-specific normalisation for automatic action unit detection. In Automatic Face and Gesture Recognition, Vol. 6. IEEE, 1--6."},{"key":"e_1_3_2_2_2_1","volume-title":"European Conference on Computer Vision. Springer, 593--608","author":"Tadas Baltruvs","year":"2014","unstructured":"Tadas Baltruvs aitis, Peter Robinson , and Louis-Philippe Morency . 2014 . Continuous conditional neural fields for structured regression . In European Conference on Computer Vision. Springer, 593--608 . Tadas Baltruvs aitis, Peter Robinson, and Louis-Philippe Morency. 2014. Continuous conditional neural fields for structured regression. In European Conference on Computer Vision. Springer, 593--608."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"crossref","unstructured":"Volker Blanz and Thomas Vetter. 1999. A morphable model for the synthesis of 3D faces. In Computer Graphics and Interactive Techniques. 187--194.  Volker Blanz and Thomas Vetter. 1999. A morphable model for the synthesis of 3D faces. In Computer Graphics and Interactive Techniques. 187--194.","DOI":"10.1145\/311535.311556"},{"key":"e_1_3_2_2_4_1","first-page":"1","article-title":"Displaced dynamic expression regression for real-time facial tracking and animation","volume":"33","author":"Cao Chen","year":"2014","unstructured":"Chen Cao , Qiming Hou , and Kun Zhou . 2014 . Displaced dynamic expression regression for real-time facial tracking and animation . Transactions on graphics , Vol. 33 , 4 (2014), 1 -- 10 . Chen Cao, Qiming Hou, and Kun Zhou. 2014. Displaced dynamic expression regression for real-time facial tracking and animation. Transactions on graphics, Vol. 33, 4 (2014), 1--10.","journal-title":"Transactions on graphics"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1109\/TVCG.2013.249","article-title":"Facewarehouse: A 3d facial expression database for visual computing","volume":"20","author":"Cao Chen","year":"2013","unstructured":"Chen Cao , Yanlin Weng , Shun Zhou , Yiying Tong , and Kun Zhou . 2013 . Facewarehouse: A 3d facial expression database for visual computing . Transactions on Visualization and Computer Graphics , Vol. 20 , 3 (2013), 413 -- 425 . Chen Cao, Yanlin Weng, Shun Zhou, Yiying Tong, and Kun Zhou. 2013. Facewarehouse: A 3d facial expression database for visual computing. Transactions on Visualization and Computer Graphics, Vol. 20, 3 (2013), 413--425.","journal-title":"Transactions on Visualization and Computer Graphics"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01151-x"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"Bindita Chaudhuri Noranart Vesdapunt and Baoyuan Wang. 2019. Joint face detection and facial motion retargeting for multiple faces. In Computer Vision and Pattern Recognition. 9719--9728.  Bindita Chaudhuri Noranart Vesdapunt and Baoyuan Wang. 2019. Joint face detection and facial motion retargeting for multiple faces. In Computer Vision and Pattern Recognition. 9719--9728.","DOI":"10.1109\/CVPR.2019.00995"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3136755.3143004"},{"key":"e_1_3_2_2_9_1","volume-title":"Palo Alto","volume":"3","author":"Friesen E","year":"1978","unstructured":"E Friesen and Paul Ekman . 1978 . Facial action coding system: a technique for the measurement of facial movement . Palo Alto , Vol. 3 (1978). E Friesen and Paul Ekman. 1978. Facial action coding system: a technique for the measurement of facial movement. Palo Alto, Vol. 3 (1978)."},{"key":"e_1_3_2_2_10_1","first-page":"1","article-title":"Reconstruction of personalized 3D face rigs from monocular video","volume":"35","author":"Garrido Pablo","year":"2016","unstructured":"Pablo Garrido , Michael Zollh\u00f6fer , Dan Casas , Levi Valgaerts , Kiran Varanasi , Patrick P\u00e9rez , and Christian Theobalt . 2016 . Reconstruction of personalized 3D face rigs from monocular video . Transactions on Graphics , Vol. 35 , 3 (2016), 1 -- 15 . Pablo Garrido, Michael Zollh\u00f6fer, Dan Casas, Levi Valgaerts, Kiran Varanasi, Patrick P\u00e9rez, and Christian Theobalt. 2016. Reconstruction of personalized 3D face rigs from monocular video. Transactions on Graphics, Vol. 35, 3 (2016), 1--15.","journal-title":"Transactions on Graphics"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"crossref","unstructured":"Kyle Genova Forrester Cole Aaron Maschinot Aaron Sarna Daniel Vlasic and William T Freeman. 2018. Unsupervised training for 3d morphable model regression. In Computer Vision and Pattern Recognition. 8377--8386.  Kyle Genova Forrester Cole Aaron Maschinot Aaron Sarna Daniel Vlasic and William T Freeman. 2018. Unsupervised training for 3d morphable model regression. In Computer Vision and Pattern Recognition. 8377--8386.","DOI":"10.1109\/CVPR.2018.00874"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2015.7284873"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"crossref","unstructured":"Philip Haeusser Alexander Mordvintsev and Daniel Cremers. 2017. Learning by Association--A Versatile Semi-Supervised Training Method for Neural Networks. In Computer Vision and Pattern Recognition. 89--98.  Philip Haeusser Alexander Mordvintsev and Daniel Cremers. 2017. Learning by Association--A Versatile Semi-Supervised Training Method for Neural Networks. In Computer Vision and Pattern Recognition. 89--98.","DOI":"10.1109\/CVPR.2017.74"},{"key":"e_1_3_2_2_14_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In Computer Vision and Pattern Recognition. 770--778.  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In Computer Vision and Pattern Recognition. 770--778."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"crossref","unstructured":"Jie Hu Li Shen and Gang Sun. 2018. Squeeze-and-excitation networks. In Computer Vision and Pattern Recognition. 7132--7141.  Jie Hu Li Shen and Gang Sun. 2018. Squeeze-and-excitation networks. In Computer Vision and Pattern Recognition. 7132--7141.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"e_1_3_2_2_16_1","volume-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy . 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 ( 2015 ). Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015)."},{"volume-title":"Automatic Face and Gesture Recognition","author":"Jeni L\u00e1szl\u00f3 A","key":"e_1_3_2_2_17_1","unstructured":"L\u00e1szl\u00f3 A Jeni , Jeffrey M Girard , Jeffrey F Cohn , and Fernando De La Torre . 2013. Continuous au intensity estimation using localized, sparse facial feature space . In Automatic Face and Gesture Recognition . IEEE , 1--7. L\u00e1szl\u00f3 A Jeni, Jeffrey M Girard, Jeffrey F Cohn, and Fernando De La Torre. 2013. Continuous au intensity estimation using localized, sparse facial feature space. In Automatic Face and Gesture Recognition. IEEE, 1--7."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Zi-Hang Jiang Qianyi Wu Keyu Chen and Juyong Zhang. 2019. Disentangled representation learning for 3D face shape. In Computer Vision and Pattern Recognition. 11957--11966.  Zi-Hang Jiang Qianyi Wu Keyu Chen and Juyong Zhang. 2019. Disentangled representation learning for 3D face shape. In Computer Vision and Pattern Recognition. 11957--11966.","DOI":"10.1109\/CVPR.2019.01223"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33191-6_36"},{"key":"e_1_3_2_2_20_1","volume-title":"Doubly sparse relevance vector machine for continuous facial behavior estimation. Transactions on Pattern Analysis and Machine Intelligence","author":"Kaltwang Sebastian","year":"2015","unstructured":"Sebastian Kaltwang , Sinisa Todorovic , and Maja Pantic . 2015a. Doubly sparse relevance vector machine for continuous facial behavior estimation. Transactions on Pattern Analysis and Machine Intelligence ( 2015 ), 1748--1761. Sebastian Kaltwang, Sinisa Todorovic, and Maja Pantic. 2015a. Doubly sparse relevance vector machine for continuous facial behavior estimation. Transactions on Pattern Analysis and Machine Intelligence (2015), 1748--1761."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"Sebastian Kaltwang Sinisa Todorovic and Maja Pantic. 2015b. Latent trees for estimating intensity of facial action units. In Computer Vision and Pattern Recognition. 296--304.  Sebastian Kaltwang Sinisa Todorovic and Maja Pantic. 2015b. Latent trees for estimating intensity of facial action units. In Computer Vision and Pattern Recognition. 296--304.","DOI":"10.1109\/CVPR.2015.7298626"},{"key":"e_1_3_2_2_22_1","volume-title":"A Style-Based Generator Architecture for Generative Adversarial Networks. Computer Vision and Pattern Recognition","author":"Karras Tero","year":"2019","unstructured":"Tero Karras , Samuli Laine , and Timo Aila . 2019. A Style-Based Generator Architecture for Generative Adversarial Networks. Computer Vision and Pattern Recognition ( 2019 ), 4401--4410. Tero Karras, Samuli Laine, and Timo Aila. 2019. A Style-Based Generator Architecture for Generative Adversarial Networks. Computer Vision and Pattern Recognition (2019), 4401--4410."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.346"},{"volume-title":"Computer Vision and Pattern Recognition-Workshops","author":"Lucey Patrick","key":"e_1_3_2_2_24_1","unstructured":"Patrick Lucey , Jeffrey F Cohn , Takeo Kanade , Jason Saragih , Zara Ambadar , and Iain Matthews . 2010. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression . In Computer Vision and Pattern Recognition-Workshops . IEEE , 94--101. Patrick Lucey, Jeffrey F Cohn, Takeo Kanade, Jason Saragih, Zara Ambadar, and Iain Matthews. 2010. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In Computer Vision and Pattern Recognition-Workshops. IEEE, 94--101."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.795"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2012.6467235"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2013.4"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2015.7284870"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2005.1521424"},{"volume-title":"International Conference on Advanced Video and Signal based Surveillance for Security, Safety and Monitoring in Smart Environments .","author":"Paysan P.","key":"e_1_3_2_2_30_1","unstructured":"P. Paysan , R. Knothe , B. Amberg , S. Romdhani , and T. Vetter . 2009. A 3D Face Model for Pose and Illumination Invariant Face Recognition . International Conference on Advanced Video and Signal based Surveillance for Security, Safety and Monitoring in Smart Environments . P. Paysan, R. Knothe, B. Amberg, S. Romdhani, and T. Vetter. 2009. A 3D Face Model for Pose and Illumination Invariant Face Recognition. International Conference on Advanced Video and Signal based Surveillance for Security, Safety and Monitoring in Smart Environments ."},{"key":"e_1_3_2_2_31_1","volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434","author":"Radford Alec","year":"2015","unstructured":"Alec Radford , Luke Metz , and Soumith Chintala . 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 ( 2015 ). Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.56"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2356192"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.101"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Soubhik Sanyal Timo Bolkart Haiwen Feng and Michael J Black. 2019. Learning to regress 3D face shape and expression from an image without 3D supervision. In Computer Vision and Pattern Recognition. 7763--7772.  Soubhik Sanyal Timo Bolkart Haiwen Feng and Michael J Black. 2019. Learning to regress 3D face shape and expression from an image without 3D supervision. In Computer Vision and Pattern Recognition. 7763--7772.","DOI":"10.1109\/CVPR.2019.00795"},{"key":"e_1_3_2_2_36_1","volume-title":"Face-to-Parameter Translation for Game Character Auto-Creation. In International Conference on Computer Vision. 161--170","author":"Shi Tianyang","year":"2019","unstructured":"Tianyang Shi , Yi Yuan , Changjie Fan , Zhengxia Zou , Zhenwei Shi , and Yong Liu . 2019 . Face-to-Parameter Translation for Game Character Auto-Creation. In International Conference on Computer Vision. 161--170 . Tianyang Shi, Yi Yuan, Changjie Fan, Zhengxia Zou, Zhenwei Shi, and Yong Liu. 2019. Face-to-Parameter Translation for Game Character Auto-Creation. In International Conference on Computer Vision. 161--170."},{"key":"e_1_3_2_2_37_1","volume-title":"Intraclass correlations: uses in assessing rater reliability. Psychological bulletin","author":"Shrout Patrick E","year":"1979","unstructured":"Patrick E Shrout and Joseph L Fleiss . 1979. Intraclass correlations: uses in assessing rater reliability. Psychological bulletin , Vol. 86 , 2 ( 1979 ), 420. Patrick E Shrout and Joseph L Fleiss. 1979. Intraclass correlations: uses in assessing rater reliability. Psychological bulletin, Vol. 86, 2 (1979), 420."},{"key":"e_1_3_2_2_38_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 ( 2014 ). Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_2_39_1","volume-title":"Unsupervised facial action unit intensity estimation via differentiable optimization. arXiv preprint arXiv:2004.05908","author":"Song Xinhui","year":"2020","unstructured":"Xinhui Song , Tianyang Shi , Tianjia Shao , Yi Yuan , Zunlei Feng , and Changjie Fan . 2020. Unsupervised facial action unit intensity estimation via differentiable optimization. arXiv preprint arXiv:2004.05908 ( 2020 ). Xinhui Song, Tianyang Shi, Tianjia Shao, Yi Yuan, Zunlei Feng, and Changjie Fan. 2020. Unsupervised facial action unit intensity estimation via differentiable optimization. arXiv preprint arXiv:2004.05908 (2020)."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"crossref","unstructured":"Ayush Tewari Michael Zollh\u00f6fer Pablo Garrido Florian Bernard Hyeongwoo Kim Patrick P\u00e9rez and Christian Theobalt. 2018. Self-supervised multi-level face model learning for monocular reconstruction at over 250 hz. In Computer Vision and Pattern Recognition. 2549--2559.  Ayush Tewari Michael Zollh\u00f6fer Pablo Garrido Florian Bernard Hyeongwoo Kim Patrick P\u00e9rez and Christian Theobalt. 2018. Self-supervised multi-level face model learning for monocular reconstruction at over 250 hz. In Computer Vision and Pattern Recognition. 2549--2559.","DOI":"10.1109\/CVPR.2018.00270"},{"key":"e_1_3_2_2_41_1","volume-title":"International Conference on Computer Vision Workshops. 1274--1283","author":"Tewari Ayush","year":"2017","unstructured":"Ayush Tewari , Michael Zollhofer , Hyeongwoo Kim , Pablo Garrido , Florian Bernard , Patrick Perez , and Christian Theobalt . 2017 . Mofa: Model-based deep convolutional face autoencoder for unsupervised monocular reconstruction . In International Conference on Computer Vision Workshops. 1274--1283 . Ayush Tewari, Michael Zollhofer, Hyeongwoo Kim, Pablo Garrido, Florian Bernard, Patrick Perez, and Christian Theobalt. 2017. Mofa: Model-based deep convolutional face autoencoder for unsupervised monocular reconstruction. In International Conference on Computer Vision Workshops. 1274--1283."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"crossref","unstructured":"Anh Tuan Tran Tal Hassner Iacopo Masi and G\u00e9rard Medioni. 2017. Regressing robust and discriminative 3D morphable models with a very deep neural network. In Computer Vision and Pattern Recognition. 5163--5172.  Anh Tuan Tran Tal Hassner Iacopo Masi and G\u00e9rard Medioni. 2017. Regressing robust and discriminative 3D morphable models with a very deep neural network. In Computer Vision and Pattern Recognition. 5163--5172.","DOI":"10.1109\/CVPR.2017.163"},{"key":"e_1_3_2_2_43_1","volume-title":"Instance normalization: The missing ingredient for fast stylization. arXiv preprint arXiv:1607.08022","author":"Ulyanov Dmitry","year":"2016","unstructured":"Dmitry Ulyanov , Andrea Vedaldi , and Victor Lempitsky . 2016. Instance normalization: The missing ingredient for fast stylization. arXiv preprint arXiv:1607.08022 ( 2016 ). Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky. 2016. Instance normalization: The missing ingredient for fast stylization. arXiv preprint arXiv:1607.08022 (2016)."},{"key":"e_1_3_2_2_44_1","volume-title":"Proc. 3rd Intern. Workshop on EMOTION (satellite of LREC): Corpora for Research on Emotion and Affect","author":"Valstar Michel","year":"2010","unstructured":"Michel Valstar and Maja Pantic . 2010 . Induced disgust, happiness and surprise: an addition to the mmi facial expression database . In Proc. 3rd Intern. Workshop on EMOTION (satellite of LREC): Corpora for Research on Emotion and Affect . Paris, France., 65. Michel Valstar and Maja Pantic. 2010. Induced disgust, happiness and surprise: an addition to the mmi facial expression database. In Proc. 3rd Intern. Workshop on EMOTION (satellite of LREC): Corpora for Research on Emotion and Affect. Paris, France., 65."},{"volume-title":"Automatic Face & Gesture Recognition","author":"Valstar Michel F","key":"e_1_3_2_2_45_1","unstructured":"Michel F Valstar , Enrique S\u00e1nchez-Lozano , Jeffrey F Cohn , L\u00e1szl\u00f3 A Jeni , Jeffrey M Girard , Zheng Zhang , Lijun Yin , and Maja Pantic . 2017. Fera 2017-addressing head pose in the third facial expression recognition and analysis challenge . In Automatic Face & Gesture Recognition . IEEE , 839--847. Michel F Valstar, Enrique S\u00e1nchez-Lozano, Jeffrey F Cohn, L\u00e1szl\u00f3 A Jeni, Jeffrey M Girard, Zheng Zhang, Lijun Yin, and Maja Pantic. 2017. Fera 2017-addressing head pose in the third facial expression recognition and analysis challenge. In Automatic Face & Gesture Recognition. IEEE, 839--847."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"crossref","unstructured":"Robert Walecki Vladimir Pavlovic Bj\u00f6rn Schuller Maja Pantic etal 2017. Deep structured learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 3405--3414.  Robert Walecki Vladimir Pavlovic Bj\u00f6rn Schuller Maja Pantic et al. 2017. Deep structured learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 3405--3414.","DOI":"10.1109\/CVPR.2017.605"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"crossref","unstructured":"Robert Walecki Ognjen Rudovic Vladimir Pavlovic and Maja Pantic. 2016. Copula ordinal regression for joint estimation of facial action unit intensity. In Computer Vision and Pattern Recognition. 4902--4910.  Robert Walecki Ognjen Rudovic Vladimir Pavlovic and Maja Pantic. 2016. Copula ordinal regression for joint estimation of facial action unit intensity. In Computer Vision and Pattern Recognition. 4902--4910.","DOI":"10.1109\/CVPR.2016.530"},{"key":"e_1_3_2_2_48_1","volume-title":"Cosface: Large margin cosine loss for deep face recognition. In Computer Vision and Pattern Recognition. 5265--5274.","author":"Wang Hao","year":"2018","unstructured":"Hao Wang , Yitong Wang , Zheng Zhou , Xing Ji , Dihong Gong , Jingchao Zhou , Zhifeng Li , and Wei Liu . 2018 . Cosface: Large margin cosine loss for deep face recognition. In Computer Vision and Pattern Recognition. 5265--5274. Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li, and Wei Liu. 2018. Cosface: Large margin cosine loss for deep face recognition. In Computer Vision and Pattern Recognition. 5265--5274."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2833032"},{"key":"e_1_3_2_2_50_1","volume-title":"Mmface: A multi-metric regression network for unconstrained face reconstruction. In Computer Vision and Pattern Recognition. 7663--7672.","author":"Yi Hongwei","year":"2019","unstructured":"Hongwei Yi , Chen Li , Qiong Cao , Xiaoyong Shen , Sheng Li , Guoping Wang , and Yu-Wing Tai . 2019 . Mmface: A multi-metric regression network for unconstrained face reconstruction. In Computer Vision and Pattern Recognition. 7663--7672. Hongwei Yi, Chen Li, Qiong Cao, Xiaoyong Shen, Sheng Li, Guoping Wang, and Yu-Wing Tai. 2019. Mmface: A multi-metric regression network for unconstrained face reconstruction. In Computer Vision and Pattern Recognition. 7663--7672."},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_20"},{"key":"e_1_3_2_2_52_1","volume-title":"Tadas Baltruvs aitis, and Louis-Philippe Morency","author":"Zadeh Amir","year":"2016","unstructured":"Amir Zadeh , Tadas Baltruvs aitis, and Louis-Philippe Morency . 2016 . Deep constrained local models for facial landmark detection. arXiv preprint arXiv:1611.08657, Vol. 3 , 5 (2016), 6. Amir Zadeh, Tadas Baltruvs aitis, and Louis-Philippe Morency. 2016. Deep constrained local models for facial landmark detection. arXiv preprint arXiv:1611.08657, Vol. 3, 5 (2016), 6."},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2014.06.002"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"crossref","unstructured":"Yong Zhang Weiming Dong Bao-Gang Hu and Qiang Ji. 2018a. Weakly-supervised deep convolutional neural network learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 2314--2323.  Yong Zhang Weiming Dong Bao-Gang Hu and Qiang Ji. 2018a. Weakly-supervised deep convolutional neural network learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 2314--2323.","DOI":"10.1109\/CVPR.2018.00246"},{"key":"e_1_3_2_2_55_1","volume-title":"Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data. In International Conference on Computer Vision. 733--742","author":"Zhang Yong","year":"2019","unstructured":"Yong Zhang , Haiyong Jiang , Baoyuan Wu , Yanbo Fan , and Qiang Ji . 2019 a . Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data. In International Conference on Computer Vision. 733--742 . Yong Zhang, Haiyong Jiang, Baoyuan Wu, Yanbo Fan, and Qiang Ji. 2019 a. Context-Aware Feature and Label Fusion for Facial Action Unit Intensity Estimation With Partially Labeled Data. In International Conference on Computer Vision. 733--742."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"crossref","unstructured":"Yong Zhang Baoyuan Wu Weiming Dong Zhifeng Li Wei Liu Bao-Gang Hu and Qiang Ji. 2019 b. Joint representation and estimator learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 3457--3466.  Yong Zhang Baoyuan Wu Weiming Dong Zhifeng Li Wei Liu Bao-Gang Hu and Qiang Ji. 2019 b. Joint representation and estimator learning for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 3457--3466.","DOI":"10.1109\/CVPR.2019.00357"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"crossref","unstructured":"Yong Zhang Rui Zhao Weiming Dong Bao-Gang Hu and Qiang Ji. 2018b. Bilateral ordinal relevance multi-instance regression for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 7034--7043.  Yong Zhang Rui Zhao Weiming Dong Bao-Gang Hu and Qiang Ji. 2018b. Bilateral ordinal relevance multi-instance regression for facial action unit intensity estimation. In Computer Vision and Pattern Recognition. 7034--7043.","DOI":"10.1109\/CVPR.2018.00735"},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.374"},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_7"},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"crossref","unstructured":"Rui Zhao Quan Gan Shangfei Wang and Qiang Ji. 2016. Facial expression intensity estimation using ordinal information. In Computer Vision and Pattern Recognition. 3466--3474.  Rui Zhao Quan Gan Shangfei Wang and Qiang Ji. 2016. Facial expression intensity estimation using ordinal information. In Computer Vision and Pattern Recognition. 3466--3474.","DOI":"10.1109\/CVPR.2016.377"},{"key":"e_1_3_2_2_61_1","unstructured":"Xiangyu Zhu Zhen Lei Xiaoming Liu Hailin Shi and Stan Z Li. 2016. Face alignment across large poses: A 3d solution. In Computer Vision and Pattern Recognition. 146--155.  Xiangyu Zhu Zhen Lei Xiaoming Liu Hailin Shi and Stan Z Li. 2016. Face alignment across large poses: A 3d solution. In Computer Vision and Pattern Recognition. 146--155."},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"crossref","unstructured":"Xiangyu Zhu Zhen Lei Junjie Yan Dong Yi and Stan Z Li. 2015. High-fidelity pose and expression normalization for face recognition in the wild. In Computer Vision and Pattern Recognition. 787--796.  Xiangyu Zhu Zhen Lei Junjie Yan Dong Yi and Stan Z Li. 2015. High-fidelity pose and expression normalization for face recognition in the wild. In Computer Vision and Pattern Recognition. 787--796.","DOI":"10.1109\/CVPR.2015.7298679"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Seattle WA USA","acronym":"MM '20"},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413955","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413955","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:32:07Z","timestamp":1750195927000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413955"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":62,"alternative-id":["10.1145\/3394171.3413955","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413955","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}