{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:22:53Z","timestamp":1750220573084,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":33,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,1,29]],"date-time":"2021-01-29T00:00:00Z","timestamp":1611878400000},"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":[[2021,1,29]]},"DOI":"10.1145\/3453800.3453819","type":"proceedings-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T23:30:12Z","timestamp":1624059012000},"page":"103-108","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Differential Residual Learning for Facial Expression Recognition"],"prefix":"10.1145","author":[{"given":"Lipeng","family":"Pu","sequence":"first","affiliation":[{"name":"Chongqing University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Chongqing University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,6,18]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"BEHZAD M. VO N. LI X. and ZHAO G. 2020. Sparsity-Aware Deep Learning for Automatic 4D Facial Expression Recognition. arXiv preprint arXiv:2002.03157.  BEHZAD M. VO N. LI X. and ZHAO G. 2020. Sparsity-Aware Deep Learning for Automatic 4D Facial Expression Recognition. arXiv preprint arXiv:2002.03157.","DOI":"10.1109\/FG47880.2020.00023"},{"volume-title":"Facial motion prior networks for facial expression recognition. In 2019 IEEE Visual Communications and Image Processing","author":"CHEN Y.","key":"e_1_3_2_1_2_1","unstructured":"CHEN , Y. , WANG , J. , CHEN , S. , SHI , Z. , and CAI , J. , 2019. Facial motion prior networks for facial expression recognition. In 2019 IEEE Visual Communications and Image Processing ( VCIP) IEEE , 1-4. CHEN, Y., WANG, J., CHEN, S., SHI, Z., and CAI, J., 2019. Facial motion prior networks for facial expression recognition. In 2019 IEEE Visual Communications and Image Processing (VCIP) IEEE, 1-4."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2917266"},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics, 249-256","author":"GLOROT X.","year":"2010","unstructured":"GLOROT , X. and BENGIO , Y. , 2010 . Understanding the difficulty of training deep feedforward neural networks . In Proceedings of the thirteenth international conference on artificial intelligence and statistics, 249-256 . GLOROT, X. and BENGIO, Y., 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics, 249-256."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130446"},{"key":"e_1_3_2_1_7_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980.","author":"KINGMA D.P.","year":"2014","unstructured":"KINGMA , D.P. and BA , J. , 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980. KINGMA, D.P. and BA, J., 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"KLASER A. MARSZA\u0141EK M. and SCHMID C. 2008. A spatio-temporal descriptor based on 3d-gradients.  KLASER A. MARSZA\u0141EK M. and SCHMID C. 2008. A spatio-temporal descriptor based on 3d-gradients.","DOI":"10.5244\/C.22.99"},{"volume-title":"Facial expression recognition in image sequences using geometric deformation features and support vector machines","author":"KOTSIA I.","key":"e_1_3_2_1_9_1","unstructured":"KOTSIA , I. and PITAS , I. , 2006. Facial expression recognition in image sequences using geometric deformation features and support vector machines . IEEE transactions on image processing 16, 1, 172-187. KOTSIA, I. and PITAS, I., 2006. Facial expression recognition in image sequences using geometric deformation features and support vector machines. IEEE transactions on image processing 16, 1, 172-187."},{"key":"e_1_3_2_1_10_1","article-title":"Deep facial expression recognition: A survey","author":"LI S.","year":"2020","unstructured":"LI , S. and DENG , W. , 2020 . Deep facial expression recognition: A survey . IEEE Transactions on Affective Computing. LI, S. and DENG, W., 2020. Deep facial expression recognition: A survey. IEEE Transactions on Affective Computing.","journal-title":"IEEE Transactions on Affective Computing."},{"issue":"2","key":"e_1_3_2_1_11_1","first-page":"227","article-title":"Expression recognition algorithm for parallel convolutional neural networks","volume":"24","author":"LINLIN X.","year":"2019","unstructured":"LINLIN , X. and ZHANGSHUMEI , Z. , 2019 . Expression recognition algorithm for parallel convolutional neural networks . Journalof ImageandGraphics 24 , 2 , 227 - 236 . LINLIN, X. and ZHANGSHUMEI, Z., 2019. Expression recognition algorithm for parallel convolutional neural networks. Journalof ImageandGraphics 24, 2, 227-236.","journal-title":"Journalof ImageandGraphics"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.327"},{"key":"e_1_3_2_1_13_1","volume-title":"Asian conference on computer vision Springer, 143-157","author":"LIU M.","year":"2014","unstructured":"LIU , M. , LI , S. , SHAN , S. , WANG , R. , and CHEN , X. , 2014 . Deeply learning deformable facial action parts model for dynamic expression analysis . In Asian conference on computer vision Springer, 143-157 . LIU, M., LI, S., SHAN, S., WANG, R., and CHEN, X., 2014. Deeply learning deformable facial action parts model for dynamic expression analysis. In Asian conference on computer vision Springer, 143-157."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"LUCEY P. COHN J.F. KANADE T. SARAGIH J. AMBADAR Z. and MATTHEWS I. 2010. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In 2010 ieee computer society conference on computer vision and pattern recognition-workshops IEEE 94-101.  LUCEY P. COHN J.F. KANADE T. SARAGIH J. AMBADAR Z. and MATTHEWS I. 2010. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In 2010 ieee computer society conference on computer vision and pattern recognition-workshops IEEE 94-101.","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00112"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477450"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69905-7_27"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2005.859075"},{"key":"e_1_3_2_1_19_1","unstructured":"PRAMERDORFER C. and KAMPEL M. 2016. Facial expression recognition using convolutional neural networks: state of the art. arXiv preprint arXiv:1612.02903.  PRAMERDORFER C. and KAMPEL M. 2016. Facial expression recognition using convolutional neural networks: state of the art. arXiv preprint arXiv:1612.02903."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130512"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.441"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2013.6475006"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"SHAN C. GONG S. and MCOWAN P.W. 2009. Facial expression recognition based on local binary patterns: A comprehensive study. Image and vision Computing 27 6 803-816.  SHAN C. GONG S. and MCOWAN P.W. 2009. Facial expression recognition based on local binary patterns: A comprehensive study. Image and vision Computing 27 6 803-816.","DOI":"10.1016\/j.imavis.2008.08.005"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.334"},{"volume-title":"Handbook of face recognition","author":"TIAN Y.-L.","key":"e_1_3_2_1_26_1","unstructured":"TIAN , Y.-L. , KANADE , T. , and COHN , J.F. , 2005. Facial expression analysis . In Handbook of face recognition Springer , 247-275. TIAN, Y.-L., KANADE, T., and COHN, J.F., 2005. Facial expression analysis. In Handbook of face recognition Springer, 247-275."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00693"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.800"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539978"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.5555\/3162631.3162760"},{"key":"e_1_3_2_1_31_1","unstructured":"ZHANG C. PLATT J.C. and VIOLA P.A. 2006. Multiple instance boosting for object detection. In Advances in neural information processing systems 1417-1424.  ZHANG C. PLATT J.C. and VIOLA P.A. 2006. Multiple instance boosting for object detection. In Advances in neural information processing systems 1417-1424."},{"key":"e_1_3_2_1_32_1","unstructured":"ZHANG C. XU X. and TU D. 2018. Face detection using improved faster rcnn. arXiv preprint arXiv:1802.02142.  ZHANG C. XU X. and TU D. 2018. Face detection using improved faster rcnn. arXiv preprint arXiv:1802.02142."},{"volume-title":"Dynamic texture recognition using local binary patterns with an application to facial expressions","author":"ZHAO","key":"e_1_3_2_1_33_1","unstructured":"ZHAO figure, G. and PIETIKAINEN , M. , 2007. Dynamic texture recognition using local binary patterns with an application to facial expressions . IEEE transactions on pattern analysis and machine intelligence 29, 6, 915-928. ZHAOfigure, G. and PIETIKAINEN, M., 2007. Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE transactions on pattern analysis and machine intelligence 29, 6, 915-928."}],"event":{"name":"ICMLSC '21: 2021 The 5th International Conference on Machine Learning and Soft Computing","acronym":"ICMLSC '21","location":"Da Nang Viet Nam"},"container-title":["2021 The 5th International Conference on Machine Learning and Soft Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3453800.3453819","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3453800.3453819","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:28:47Z","timestamp":1750195727000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3453800.3453819"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,29]]},"references-count":33,"alternative-id":["10.1145\/3453800.3453819","10.1145\/3453800"],"URL":"https:\/\/doi.org\/10.1145\/3453800.3453819","relation":{},"subject":[],"published":{"date-parts":[[2021,1,29]]},"assertion":[{"value":"2021-06-18","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}