{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:23:26Z","timestamp":1750220606111,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":34,"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":"Beijing Academy of Artificial Intelligence"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413919","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T12:26:18Z","timestamp":1602505578000},"page":"556-564","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Dual-Structure Disentangling Variational Generation for Data-Limited Face Parsing"],"prefix":"10.1145","author":[{"given":"Peipei","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Automation Chinese Academy of Sciences & JD AI Research, Beijing, China"}]},{"given":"Yinglu","family":"Liu","sequence":"additional","affiliation":[{"name":"JD AI Research, Beijing, China"}]},{"given":"Hailin","family":"Shi","sequence":"additional","affiliation":[{"name":"JD AI Research, Beijing, China"}]},{"given":"Xiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Institute of Automation Chinese Academy of Sciences, Beijing, China"}]},{"given":"Yibo","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Automation Chinese Academy of Sciences, Beijing, China"}]},{"given":"Ran","family":"He","sequence":"additional","affiliation":[{"name":"Institute of Automation Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"}]},{"given":"Zhenan","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Automation Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Support vector machines with the ramp loss and the hard margin loss. Operations research 59, 2","author":"Brooks J Paul","year":"2011","unstructured":"J Paul Brooks . 2011. Support vector machines with the ramp loss and the hard margin loss. Operations research 59, 2 ( 2011 ), 467--479. J Paul Brooks. 2011. Support vector machines with the ramp loss and the hard margin loss. Operations research 59, 2 (2011), 467--479."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Jaehoon Choi Taekyung Kim and Changick Kim. 2019. Self-ensembling with GAN-based data augmentation for domain adaptation in semantic segmentation. In ICCV.  Jaehoon Choi Taekyung Kim and Changick Kim. 2019. Self-ensembling with GAN-based data augmentation for domain adaptation in semantic segmentation. In ICCV.","DOI":"10.1109\/ICCV.2019.00693"},{"key":"e_1_3_2_2_3_1","volume-title":"huaibo Huang, and Ran He","author":"Fu Chaoyou","year":"2019","unstructured":"Chaoyou Fu , Xiang Wu , Yibo Hu , huaibo Huang, and Ran He . 2019 . Dual variational generation for low shot heterogeneous face recognition. In NeurIPS. Chaoyou Fu, Xiang Wu, Yibo Hu, huaibo Huang, and Ran He. 2019. Dual variational generation for low shot heterogeneous face recognition. In NeurIPS."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Aritra Ghosh Himanshu Kumar and PS Sastry. 2017. Robust loss functions under label noise for deep neural networks. In AAAI.  Aritra Ghosh Himanshu Kumar and PS Sastry. 2017. Robust loss functions under label noise for deep neural networks. In AAAI.","DOI":"10.1609\/aaai.v31i1.10894"},{"key":"e_1_3_2_2_5_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 NeurIPS.  Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In NeurIPS."},{"key":"e_1_3_2_2_6_1","unstructured":"Tianchu Guo Youngsung Kim Hui Zhang Deheng Qian ByungIn Yoo Jingtao Xu Dongqing Zou Jae-Joon Han and Changkyu Choi. 2018. Residual encoder decoder network and adaptive prior for face parsing. In AAAI.  Tianchu Guo Youngsung Kim Hui Zhang Deheng Qian ByungIn Yoo Jingtao Xu Dongqing Zou Jae-Joon Han and Changkyu Choi. 2018. Residual encoder decoder network and adaptive prior for face parsing. In AAAI."},{"key":"e_1_3_2_2_7_1","unstructured":"Yandong Guo Zhang Lei Yuxiao Hu Xiaodong He and Jianfeng Gao. 2016. MSCeleb- 1M: A dataset and benchmark for large-scale face recognition. In ECCV.  Yandong Guo Zhang Lei Yuxiao Hu Xiaodong He and Jianfeng Gao. 2016. MSCeleb- 1M: A dataset and benchmark for large-scale face recognition. In ECCV."},{"key":"e_1_3_2_2_8_1","unstructured":"Huaibo Huang Zhihang Li Ran He Zhenan Sun and Tieniu Tan. 2018. IntroVAE: Introspective variational autoencoders for photographic image synthesis. In NeurIPS.  Huaibo Huang Zhihang Li Ran He Zhenan Sun and Tieniu Tan. 2018. IntroVAE: Introspective variational autoencoders for photographic image synthesis. In NeurIPS."},{"key":"e_1_3_2_2_9_1","volume-title":"Auggan: Cross domain adaptation with gan-based data augmentation. In ECCV.","author":"Huang Shengwei","year":"2018","unstructured":"Shengwei Huang , Che-Tsung Lin , Chen Shuping , Yenyi Wu , Pohao Hsu , and Shanghong Lai . 2018 . Auggan: Cross domain adaptation with gan-based data augmentation. In ECCV. Shengwei Huang, Che-Tsung Lin, Chen Shuping, Yenyi Wu, Pohao Hsu, and Shanghong Lai. 2018. Auggan: Cross domain adaptation with gan-based data augmentation. In ECCV."},{"key":"e_1_3_2_2_10_1","volume-title":"Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels. In ICML.","author":"Jiang Lu","year":"2017","unstructured":"Lu Jiang , Zhengyuan Zhou , Thomas Leung , Li-Jia Li , and Li Fei-Fei . 2017 . Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels. In ICML. Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, and Li Fei-Fei. 2017. Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels. In ICML."},{"key":"e_1_3_2_2_11_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_2_12_1","unstructured":"Vuong Le Jonathan Brandt Zhe Lin Lubomir Bourdev and Thomas S Huang. 2012. Interactive facial feature localization. In ECCV.  Vuong Le Jonathan Brandt Zhe Lin Lubomir Bourdev and Thomas S Huang. 2012. Interactive facial feature localization. In ECCV."},{"key":"e_1_3_2_2_13_1","volume-title":"MaskGAN: Towards diverse and interactive facial image manipulation. arXiv preprint arXiv:1907.11922","author":"Lee Cheng-Han","year":"2019","unstructured":"Cheng-Han Lee , Ziwei Liu , LingyunWu, and Ping Luo . 2019. MaskGAN: Towards diverse and interactive facial image manipulation. arXiv preprint arXiv:1907.11922 ( 2019 ). Cheng-Han Lee, Ziwei Liu, LingyunWu, and Ping Luo. 2019. MaskGAN: Towards diverse and interactive facial image manipulation. arXiv preprint arXiv:1907.11922 (2019)."},{"key":"e_1_3_2_2_14_1","unstructured":"Jinpeng Lin Hao Yang Dong Chen Ming Zeng Fang Wen and Lu Yuan. 2019. Face parsing with RoI Tanh-warping. In CVPR.  Jinpeng Lin Hao Yang Dong Chen Ming Zeng Fang Wen and Lu Yuan. 2019. Face parsing with RoI Tanh-warping. In CVPR."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"crossref","unstructured":"Sifei Liu Jianping Shi Ji Liang and Ming-Hsuan Yang. 2017. Face parsing via recurrent propagation. In BMVC.  Sifei Liu Jianping Shi Ji Liang and Ming-Hsuan Yang. 2017. Face parsing via recurrent propagation. In BMVC.","DOI":"10.5244\/C.31.8"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Sifei Liu Jimei Yang Chang Huang and Ming-Hsuan Yang. 2015. Multi-objective convolutional learning for face labeling. In CVPR.  Sifei Liu Jimei Yang Chang Huang and Ming-Hsuan Yang. 2015. Multi-objective convolutional learning for face labeling. In CVPR.","DOI":"10.1109\/CVPR.2015.7298967"},{"key":"e_1_3_2_2_17_1","unstructured":"Shuangting Liu Jiaqi Zhang Yuxin Chen Yifan Liu Zengchang Qin and Tao Wan. 2019. Pixel level data augmentation for semantic image segmentation using generative adversarial networks. In ICASSP.  Shuangting Liu Jiaqi Zhang Yuxin Chen Yifan Liu Zengchang Qin and Tao Wan. 2019. Pixel level data augmentation for semantic image segmentation using generative adversarial networks. In ICASSP."},{"key":"e_1_3_2_2_18_1","unstructured":"Yinglu Liu Hailin Shi Yue Si Hao Shen Xiaobo Wang and Tao Mei. 2020. A high-efficiency framework for constructing large-scale face parsing benchmark. In AAAI.  Yinglu Liu Hailin Shi Yue Si Hao Shen Xiaobo Wang and Tao Mei. 2020. A high-efficiency framework for constructing large-scale face parsing benchmark. In AAAI."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Ziwei Liu Ping Luo XiaogangWang and Xiaoou Tang. 2015. Deep learning face attributes in the wild. In ICCV.  Ziwei Liu Ping Luo XiaogangWang and Xiaoou Tang. 2015. Deep learning face attributes in the wild. In ICCV.","DOI":"10.1109\/ICCV.2015.425"},{"key":"e_1_3_2_2_20_1","unstructured":"Hamed Masnadi-Shirazi and Nuno Vasconcelos. 2009. On the design of loss functions for classification: theory robustness to outliers and savageboost. In NeurIPS.  Hamed Masnadi-Shirazi and Nuno Vasconcelos. 2009. On the design of loss functions for classification: theory robustness to outliers and savageboost. In NeurIPS."},{"key":"e_1_3_2_2_21_1","unstructured":"Danilo Jimenez Rezende Shakir Mohamed and Daan Wierstra. 2014. Stochastic backpropagation and approximate inference in deep generative models. In ICML.  Danilo Jimenez Rezende Shakir Mohamed and Daan Wierstra. 2014. Stochastic backpropagation and approximate inference in deep generative models. In ICML."},{"key":"e_1_3_2_2_22_1","unstructured":"Yanyao Shen and Sujay Sanghavi. 2019. Learning with bad training data via iterative trimmed loss minimization. In ICML.  Yanyao Shen and Sujay Sanghavi. 2019. Learning with bad training data via iterative trimmed loss minimization. In ICML."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Brandon M. Smith Zhang Li Jonathan Brandt Lin Zhe and Jianchao Yang. 2013. Exemplar-based face parsing. In CVPR.  Brandon M. Smith Zhang Li Jonathan Brandt Lin Zhe and Jianchao Yang. 2013. Exemplar-based face parsing. In CVPR.","DOI":"10.1109\/CVPR.2013.447"},{"key":"e_1_3_2_2_24_1","unstructured":"Brendan Van Rooyen Aditya Menon and Robert C Williamson. 2015. Learning with symmetric label noise: The importance of being unhinged. In NeurIPS.  Brendan Van Rooyen Aditya Menon and Robert C Williamson. 2015. Learning with symmetric label noise: The importance of being unhinged. In NeurIPS."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi and James Bailey. 2019. Symmetric cross entropy for robust learning with noisy labels. In ICCV.  Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi and James Bailey. 2019. Symmetric cross entropy for robust learning with noisy labels. In ICCV.","DOI":"10.1109\/ICCV.2019.00041"},{"key":"e_1_3_2_2_26_1","first-page":"1","article-title":"A light cnn for deep face representation with noisy labels","volume":"99","author":"Wu Xiang","year":"2015","unstructured":"Xiang Wu , Ran He , Zhenan Sun , and Tieniu Tan . 2015 . A light cnn for deep face representation with noisy labels . IEEE Transactions on Information Forensics Security PP , 99 (2015), 1 -- 1 . Xiang Wu, Ran He, Zhenan Sun, and Tieniu Tan. 2015. A light cnn for deep face representation with noisy labels. IEEE Transactions on Information Forensics Security PP, 99 (2015), 1--1.","journal-title":"IEEE Transactions on Information Forensics Security PP"},{"key":"e_1_3_2_2_27_1","volume-title":"Shinya and Takeharu Eda","author":"Yamaguchi Sekitoshi Kanai","year":"2020","unstructured":"Sekitoshi Kanai Yamaguchi , Shinya and Takeharu Eda . 2020 . Effective data augmentation with multi-domain learning GANs. In AAAI. Sekitoshi Kanai Yamaguchi, Shinya and Takeharu Eda. 2020. Effective data augmentation with multi-domain learning GANs. In AAAI."},{"key":"e_1_3_2_2_28_1","unstructured":"Zhilu Zhang and Mert Sabuncu. 2018. Generalized cross entropy loss for training deep neural networks with noisy labels. In NeurIPS.  Zhilu Zhang and Mert Sabuncu. 2018. Generalized cross entropy loss for training deep neural networks with noisy labels. In NeurIPS."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"Amy Zhao Guha Balakrishnan Fredo Durand John V Guttag and Adrian V Dalca. 2019. Data augmentation using learned transformations for one-shot medical image segmentation. In CVPR.  Amy Zhao Guha Balakrishnan Fredo Durand John V Guttag and Adrian V Dalca. 2019. Data augmentation using learned transformations for one-shot medical image segmentation. In CVPR.","DOI":"10.1109\/CVPR.2019.00874"},{"key":"e_1_3_2_2_30_1","unstructured":"Hengshuang Zhao Jianping Shi Xiaojuan Qi XiaogangWang and Jiaya Jia. 2017. Pyramid scene parsing network. In CVPR.  Hengshuang Zhao Jianping Shi Xiaojuan Qi XiaogangWang and Jiaya Jia. 2017. Pyramid scene parsing network. In CVPR."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"crossref","unstructured":"Wei Zhen Sun Yao Jinqiao Wang Hanjiang Lai and Liu Si. 2017. Learning adaptive receptive fields for deep image parsing network. In CVPR.  Wei Zhen Sun Yao Jinqiao Wang Hanjiang Lai and Liu Si. 2017. Learning adaptive receptive fields for deep image parsing network. In CVPR.","DOI":"10.1109\/CVPR.2017.420"},{"key":"e_1_3_2_2_32_1","volume-title":"Functional gradient ascent for probit regression. Pattern recognition 45, 12","author":"Zheng Songfeng","year":"2012","unstructured":"Songfeng Zheng and Weixiang Liu . 2012. Functional gradient ascent for probit regression. Pattern recognition 45, 12 ( 2012 ), 4428--4437. Songfeng Zheng and Weixiang Liu. 2012. Functional gradient ascent for probit regression. Pattern recognition 45, 12 (2012), 4428--4437."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"crossref","unstructured":"Yisu Zhou Xiaolin Hu and Bo Zhang. 2015. Interlinked convolutional neural networks for face parsing. In ISNN.  Yisu Zhou Xiaolin Hu and Bo Zhang. 2015. Interlinked convolutional neural networks for face parsing. In ISNN.","DOI":"10.1007\/978-3-319-25393-0_25"},{"key":"e_1_3_2_2_34_1","unstructured":"Xinyue Zhu Yifan Liu Jiahong Li and Litao Wan. 2018. Emotion classification with data augmentation using generative adversarial networks. In PAKDD.  Xinyue Zhu Yifan Liu Jiahong Li and Litao Wan. 2018. Emotion classification with data augmentation using generative adversarial networks. In PAKDD."}],"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\/3394171.3413919","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413919","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:32:06Z","timestamp":1750195926000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413919"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":34,"alternative-id":["10.1145\/3394171.3413919","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413919","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"}}]}}