{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T08:17:37Z","timestamp":1780474657254,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"funding of National Key R & D Program of China","award":["2021YFB3300100"],"award-info":[{"award-number":["2021YFB3300100"]}]},{"name":"Young Elite Scientist Sponsorship Program of China Association for Science and Technology","award":["YESS20200140"],"award-info":[{"award-number":["YESS20200140"]}]},{"name":"Young Elite Scientist Sponsorship Program of Beijing Association for Science and Technology","award":["BYESS2021178"],"award-info":[{"award-number":["BYESS2021178"]}]},{"name":"Natural Science Foundation of China under Grant","award":["62222606"],"award-info":[{"award-number":["62222606"]}]},{"name":"National Nature Fund","award":["62102039,62006244"],"award-info":[{"award-number":["62102039,62006244"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3611993","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:40Z","timestamp":1698391660000},"page":"1863-1873","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Single-Stage Multi-human Parsing via Point Sets and Center-based Offsets"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3040-3674","authenticated-orcid":false,"given":"Jiaming","family":"Chu","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4855-2464","authenticated-orcid":false,"given":"Lei","family":"Jin","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2195-0043","authenticated-orcid":false,"given":"Xiaojin","family":"Fan","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7170-4764","authenticated-orcid":false,"given":"Yinglei","family":"Teng","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2812-8781","authenticated-orcid":false,"given":"Yunchao","family":"Wei","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7259-9823","authenticated-orcid":false,"given":"Yuqiang","family":"Fang","sequence":"additional","affiliation":[{"name":"Space Engineering University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6801-0510","authenticated-orcid":false,"given":"Junliang","family":"Xing","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3508-756X","authenticated-orcid":false,"given":"Jian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of North Electronic Equipment, Intelligent Game and Decision Laboratory & Peng Cheng Laboratory, Beijing; Beijing; Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Yalan Qin A Hanzhou Wu A Jian Zhao B and Guorui Feng A. [n. d.]. Enforced block diagonal subspace clustering with closed form solution. Pattern Recognition 130 ([n. d.]).","DOI":"10.1016\/j.patcog.2022.108791"},{"key":"e_1_3_2_2_2_1","volume-title":"YOLACT: Real-Time Instance Segmentation. ICCV","author":"Bolya Daniel","year":"2019","unstructured":"Daniel Bolya, Chong Zhou, Fanyi Xiao, and Yong Jae Lee. 2019. YOLACT: Real-Time Instance Segmentation. ICCV (2019)."},{"key":"e_1_3_2_2_3_1","volume-title":"KPN-MFI: A Kernel Prediction Network with Multi-frame Interaction for Video Inverse Tone Mapping. IJCAI","author":"Cao Gaofeng","year":"2022","unstructured":"Gaofeng Cao, Fei Zhou, Han Yan, Anjie Wang, and Leidong Fan. 2022. KPN-MFI: A Kernel Prediction Network with Multi-frame Interaction for Video Inverse Tone Mapping. IJCAI (2022)."},{"key":"e_1_3_2_2_4_1","volume-title":"Chen Change Loy, and Dahua Lin","author":"Chen Kai","year":"2019","unstructured":"Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin. 2019. MMDetection: Open MMLab Detection Toolbox and Benchmark. arXiv preprint arXiv:1906.07155 (2019)."},{"key":"e_1_3_2_2_5_1","volume-title":"AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection. IJCAI","author":"Chen Zehui","year":"2022","unstructured":"Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinghong Jiang, Feng Zhao, Bolei Zhou, and Hang Zhao. 2022. AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection. IJCAI (2022)."},{"key":"e_1_3_2_2_6_1","volume-title":"Instance-sensitive Fully Convolutional Networks. ECCV","author":"Dai Jifeng","year":"2016","unstructured":"Jifeng Dai, Kaiming He, Yi Li, Shaoqing Ren, and Jian Sun. 2016. Instance-sensitive Fully Convolutional Networks. ECCV (2016)."},{"key":"e_1_3_2_2_7_1","volume-title":"Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation. IJCAI","author":"Dong Hexin","year":"2022","unstructured":"Hexin Dong, Zifan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, and Li Zhang. 2022. Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation. IJCAI (2022)."},{"key":"e_1_3_2_2_8_1","volume-title":"Rethinking 2D\/3D Networks for Anisotropic Medical Image Segmentation. IJCAI","author":"Dong Zhangfu","year":"2022","unstructured":"Zhangfu Dong, Yuting He, Xiaoming Qi, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Guanyu Yang, and Shuo Li. 2022. MNet: Rethinking 2D\/3D Networks for Anisotropic Medical Image Segmentation. IJCAI (2022)."},{"key":"e_1_3_2_2_9_1","volume-title":"Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression. CVPR","author":"Geng Zigang","year":"2021","unstructured":"Zigang Geng, Ke Sun, Bin Xiao, Zhaoxiang Zhang, and Jingdong Wang. 2021. Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression. CVPR (2021)."},{"key":"e_1_3_2_2_10_1","volume-title":"arXiv: Computer Vision and Pattern Recognition","author":"Girshick Ross","year":"2015","unstructured":"Ross Girshick. 2015. Fast R-CNN. arXiv: Computer Vision and Pattern Recognition (2015)."},{"key":"e_1_3_2_2_11_1","volume-title":"Instance-level Human Parsing via Part Grouping Network. ECCV","author":"Gong Ke","year":"2018","unstructured":"Ke Gong, Xiaodan Liang, Yicheng Li, Yimin Chen, Ming Yang, and Liang Lin. 2018. Instance-level Human Parsing via Part Grouping Network. ECCV (2018)."},{"key":"e_1_3_2_2_12_1","volume-title":"DensePose: Dense Human Pose Estimation in the Wild. CVPR","author":"Guler Riza Alp","year":"2018","unstructured":"Riza Alp Guler, Natalia Neverova, and Iasonas Kokkinos. 2018. DensePose: Dense Human Pose Estimation in the Wild. CVPR (2018)."},{"key":"e_1_3_2_2_13_1","unstructured":"Kaiming He Georgia Gkioxari Piotr Doll\u00e1r and Ross Girshick. 2017. Mask R-CNN. TPAMI (2017)."},{"key":"e_1_3_2_2_14_1","volume-title":"Deep Residual Learning for Image Recognition. CVPR","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. CVPR (2016)."},{"key":"e_1_3_2_2_15_1","volume-title":"Liang Gou, and Liu Ren.","author":"He Wenbin","year":"2022","unstructured":"Wenbin He, William Surmeier, Arvind Kumar Shekar, Liang Gou, and Liu Ren. 2022. Self-supervised Semantic Segmentation Grounded in Visual Concepts. IJCAI (2022)."},{"key":"e_1_3_2_2_16_1","volume-title":"Learning Semantic Neural Tree for Human Parsing. ECCV","author":"Ji Ruyi","year":"2019","unstructured":"Ruyi Ji, Dawei Du, Libo Zhang, Longyin Wen, Yanjun Wu, Chen Zhao, Feiyue Huang, and Siwei Lyu. 2019. Learning Semantic Neural Tree for Human Parsing. ECCV (2019)."},{"key":"e_1_3_2_2_17_1","volume-title":"Grouping by center: Predicting centripetal offsets for the bottom-up human pose estimation","author":"Jin Lei","year":"2022","unstructured":"Lei Jin, Xiaojuan Wang, Xuecheng Nie, Luoqi Liu, Yandong Guo, and Jian Zhao. 2022. Grouping by center: Predicting centripetal offsets for the bottom-up human pose estimation. IEEE TMM (2022)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3282139"},{"key":"e_1_3_2_2_19_1","volume-title":"A Style-Based Generator Architecture for Generative Adversarial Networks. TPAMI","author":"Karras Tero","year":"2018","unstructured":"Tero Karras, Samuli Laine, and Timo Aila. 2018. A Style-Based Generator Architecture for Generative Adversarial Networks. TPAMI (2018)."},{"key":"e_1_3_2_2_20_1","volume-title":"Single-Stage is Enough: Multi-Person Absolute 3D Pose Estimation. CVPR","author":"Lei Jin","year":"2022","unstructured":"Jin Lei, Chenyang Xu, Xiaojuan Wang, Yabo Xiao, Yandong Guo, Xuecheng Nie, and Jian Zhao. 2022. Single-Stage is Enough: Multi-Person Absolute 3D Pose Estimation. CVPR (2022)."},{"key":"e_1_3_2_2_21_1","volume-title":"IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement. IJCAI","author":"Li Jie","year":"2021","unstructured":"Jie Li, Laiyan Ding, and Rui Huang. 2021. IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement. IJCAI (2021)."},{"key":"e_1_3_2_2_22_1","volume-title":"Multi-human Parsing with a Graph-based Generative Adversarial Model. ACM TOMM","author":"Li Jianshu","year":"2021","unstructured":"Jianshu Li, Jian Zhao, Congyan Lang, Yidong Li, Yunchao Wei, Guodong Guo, Terence Sim, Shuicheng Yan, and Jiashi Feng. 2021. Multi-human Parsing with a Graph-based Generative Adversarial Model. ACM TOMM (2021)."},{"key":"e_1_3_2_2_23_1","unstructured":"Jianshu Li Jian Zhao Yunchao Wei Congyan Lang Yidong Li and Jiashi Feng. 2017. Towards RealWorld Human Parsing: Multiple-Human Parsing in the Wild."},{"key":"e_1_3_2_2_24_1","volume-title":"Feature Pyramid Networks for Object Detection. CVPR","author":"Lin Tsung-Yi","year":"2016","unstructured":"Tsung-Yi Lin, Piotr Doll\u00e1r, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie. 2016. Feature Pyramid Networks for Object Detection. CVPR (2016)."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"e_1_3_2_2_26_1","volume-title":"Microsoft COCO: Common Objects in Context. european conference on computer vision","author":"Lin Tsung-Yi","year":"2014","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. european conference on computer vision (2014)."},{"key":"e_1_3_2_2_27_1","volume-title":"Eric Frank, Alex Sergeev, and Jason Yosinski.","author":"Liu Rosanne","year":"2018","unstructured":"Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, and Jason Yosinski. 2018. An intriguing failing of convolutional neural networks and the CoordConv solution. NeurIPS (2018)."},{"key":"e_1_3_2_2_28_1","volume-title":"Fully Convolutional Networks for Semantic Segmentation","author":"Long Jonathan","year":"2014","unstructured":"Jonathan Long, Evan Shelhamer, and Trevor Darrell. 2014. Fully Convolutional Networks for Semantic Segmentation. IEEE TPAMI (2014)."},{"key":"e_1_3_2_2_29_1","volume-title":"Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation. CVPR","author":"McNally William","year":"2021","unstructured":"William McNally, Kanav Vats, Alexander Wong, and John McPhee. 2021. Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation. CVPR (2021)."},{"key":"e_1_3_2_2_30_1","volume-title":"V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. ICCV","author":"Milletari Fausto","year":"2016","unstructured":"Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi. 2016. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. ICCV (2016)."},{"key":"e_1_3_2_2_31_1","volume-title":"Marc Proesmans, and Luc Van Gool.","author":"Neven Davy","year":"2019","unstructured":"Davy Neven, Bert De Brabandere, Marc Proesmans, and Luc Van Gool. 2019. Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth. CVPR (2019)."},{"key":"e_1_3_2_2_32_1","volume-title":"BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation. IJCAI","author":"Ni Zhen-Liang","year":"2020","unstructured":"Zhen-Liang Ni, Gui-Bin Bian, Guan'an Wang, Xiao-Hu Zhou, Zeng-Guang Hou, Xiao-Liang Xie, Zhen Li, and Yu-Han Wang. 2020. BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation. IJCAI (2020)."},{"key":"e_1_3_2_2_33_1","volume-title":"Single-Stage Multi-Person Pose Machines. ICCV","author":"Nie Xuecheng","year":"2019","unstructured":"Xuecheng Nie, Jiashi Feng, Jianfeng Zhang, and Shuicheng Yan. 2019. Single-Stage Multi-Person Pose Machines. ICCV (2019)."},{"key":"e_1_3_2_2_34_1","volume-title":"Enforced Block Diagonal Subspace Clustering with Closed Form Solution. Pattern Recognition","author":"Qin Yalan","year":"2022","unstructured":"Yalan Qin, Hanzhou Wu, Jian Zhao, and Guorui Feng. 2022. Enforced Block Diagonal Subspace Clustering with Closed Form Solution. Pattern Recognition (2022)."},{"key":"e_1_3_2_2_35_1","volume-title":"YOLOv3: An Incremental Improvement. arXiv: Computer Vision and Pattern Recognition","author":"Redmon Joseph","year":"2018","unstructured":"Joseph Redmon and Ali Farhadi. 2018. YOLOv3: An Incremental Improvement. arXiv: Computer Vision and Pattern Recognition (2018)."},{"key":"e_1_3_2_2_36_1","volume-title":"Devil in the Details: Towards Accurate Single and Multiple Human Parsing. AAAI","author":"Ruan Tao","year":"2019","unstructured":"Tao Ruan, Ting Liu, Zilong Huang, Yunchao Wei, Shikui Wei, and Yao Zhao. 2019. Devil in the Details: Towards Accurate Single and Multiple Human Parsing. AAAI (2019)."},{"key":"e_1_3_2_2_37_1","volume-title":"AdaptIS: Adaptive Instance Selection Network. ICCV","author":"Sofiiuk Konstantin","year":"2019","unstructured":"Konstantin Sofiiuk, Olga Barinova, and Anton Konushin. 2019. AdaptIS: Adaptive Instance Selection Network. ICCV (2019)."},{"key":"e_1_3_2_2_38_1","volume-title":"Conditional Convolutions for Instance Segmentation. arXiv: Computer Vision and Pattern Recognition","author":"Tian Zhi","year":"2020","unstructured":"Zhi Tian, Chunhua Shen, and Hao Chen. 2020. Conditional Convolutions for Instance Segmentation. arXiv: Computer Vision and Pattern Recognition (2020)."},{"key":"e_1_3_2_2_39_1","volume-title":"SOLO: Segmenting Objects by Locations. ECCV","author":"Wang Xinlong","year":"2019","unstructured":"Xinlong Wang, Tao Kong, Chunhua Shen, Yuning Jiang, and Lei Li. 2019. SOLO: Segmenting Objects by Locations. ECCV (2019)."},{"key":"e_1_3_2_2_40_1","volume-title":"SOLOv2: Dynamic and Fast Instance Segmentation. NeurIPS","author":"Wang Xinlong","year":"2020","unstructured":"Xinlong Wang, Rufeng Zhang, Tao Kong, Lei Li, and Chunhua Shen. 2020. SOLOv2: Dynamic and Fast Instance Segmentation. NeurIPS (2020)."},{"key":"e_1_3_2_2_41_1","volume-title":"Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. ACM Transactions on Knowledge Discovery from Data","author":"Xiong Haoyi","year":"2022","unstructured":"Haoyi Xiong, Ruosi Wan, Jian Zhao, Zeyu Chen, Xingjian Li, Zhanxing Zhu, and Jun Huan. 2022. GrOD : Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. ACM Transactions on Knowledge Discovery from Data (2022)."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"crossref","unstructured":"Nan Xue Tianfu Wu Gui-Song Xia and Liangpei Zhang. 2022. Learning Local-Global Contextual Adaptation for Multi-Person Pose Estimation. (2022) 13065--13074.","DOI":"10.1109\/CVPR52688.2022.01272"},{"key":"e_1_3_2_2_43_1","volume-title":"CondConv: Conditionally Parameterized Convolutions for Efficient Inference. NeurIPS","author":"Yang Brandon","year":"2019","unstructured":"Brandon Yang, Gabriel Bender, Quoc V. Le, and Jiquan Ngiam. 2019. CondConv: Conditionally Parameterized Convolutions for Efficient Inference. NeurIPS (2019)."},{"key":"e_1_3_2_2_44_1","volume-title":"Renovating Parsing R-CNN for Accurate Multiple Human Parsing. ECCV","author":"Yang Lu","year":"2020","unstructured":"Lu Yang, Qing Song, ZhihuiWang, Mengjie Hu, Chun Liu, Xin Xueshi, JiaWenhe, and Songcen Xu. 2020. Renovating Parsing R-CNN for Accurate Multiple Human Parsing. ECCV (2020)."},{"key":"e_1_3_2_2_45_1","volume-title":"Parsing R-CNN for Instance-Level Human Analysis. CVPR","author":"Yang Lu","year":"2018","unstructured":"Lu Yang, Qing Song, Zhihui Wang, and Ming Jiang. 2018. Parsing R-CNN for Instance-Level Human Analysis. CVPR (2018)."},{"key":"e_1_3_2_2_46_1","volume-title":"EmbedMask: Embedding Coupling for Instance Segmentation. IJCAI","author":"Ying Hui","year":"2021","unstructured":"Hui Ying, Zhaojin Huang, Shu Liu, Tianjia Shao, and Kun Zhou. 2021. EmbedMask: Embedding Coupling for Instance Segmentation. IJCAI (2021)."},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"crossref","unstructured":"Sanyi Zhang Xiaochun Cao Guo-Jun Qi Zhanjie Song and Jie Zhou. 2022. AIParsing: Anchor-free Instance-level Human Parsing. TIP.","DOI":"10.1109\/TIP.2022.3192989"},{"key":"e_1_3_2_2_48_1","volume-title":"Sequential 3D Human Pose Estimation Using Adaptive Point Cloud Sampling Strategy. IJCAI","author":"Zhang Zihao","year":"2021","unstructured":"Zihao Zhang, Lei Hu, Xiaoming Deng, and Shihong Xia. 2021. Sequential 3D Human Pose Estimation Using Adaptive Point Cloud Sampling Strategy. IJCAI (2021)."},{"key":"e_1_3_2_2_49_1","volume-title":"Distilling Inter-Class Distance for Semantic Segmentation. IJCAI","author":"Zhang Zhengbo","year":"2022","unstructured":"Zhengbo Zhang, Chunluan Zhou, and Zhigang Tu. 2022. Distilling Inter-Class Distance for Semantic Segmentation. IJCAI (2022)."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"crossref","unstructured":"Fang Zhao Jian Zhao Shuicheng Yan and Jiashi Feng. 2018. Dynamic Conditional Networks for Few-Shot Learning. (2018).","DOI":"10.1007\/978-3-030-01267-0_2"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"crossref","unstructured":"Fang Zhao Jian Zhao Shuicheng Yan and Jiashi Feng. 2018. Dynamic Conditional Networks for Few-Shot Learning. (2018).","DOI":"10.1007\/978-3-030-01267-0_2"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240509"},{"key":"e_1_3_2_2_53_1","volume-title":"Fine-Grained Multi-human Parsing. IJCV","author":"Zhao Jian","year":"2020","unstructured":"Jian Zhao, Jianshu Li, Hengzhu Liu, Shuicheng Yan, and Jiashi Feng. 2020. Fine-Grained Multi-human Parsing. IJCV (2020)."},{"key":"e_1_3_2_2_54_1","volume-title":"Self-Supervised Neural Aggregation Networks for Human Parsing. CVPR","author":"Zhao Jian","year":"2017","unstructured":"Jian Zhao, Jianshu Li, Xuecheng Nie, Fang Zhao, Yunpeng Chen, Zhecan Wang, Jiashi Feng, and Shuicheng Yan. 2017. Self-Supervised Neural Aggregation Networks for Human Parsing. CVPR (2017)."},{"key":"e_1_3_2_2_55_1","volume-title":"Procedings of the British Machine Vision Conference","author":"Jianshu Li Jian ZHAO","year":"2017","unstructured":"Jian ZHAO, Jianshu Li, Fang Zhao, Xuecheng Nie, Yunpeng Chen, Shuicheng Yan, and Jiashi Feng. 2017. Marginalized CNN: Learning Deep Invariant Representations.. In Procedings of the British Machine Vision Conference 2017."},{"key":"e_1_3_2_2_56_1","volume-title":"Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing. CVPR","author":"Zhou Tianfei","year":"2021","unstructured":"Tianfei Zhou, Wenguan Wang, Si Liu, Yi Yang, and Luc Van Gool. 2021. Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing. CVPR (2021)."},{"key":"e_1_3_2_2_57_1","volume-title":"Better Results. CVPR","author":"Zhu Xizhou","year":"2018","unstructured":"Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai. 2018. Deformable ConvNets v2: More Deformable, Better Results. CVPR (2018)."}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611993","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3611993","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:12:10Z","timestamp":1755821530000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611993"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":57,"alternative-id":["10.1145\/3581783.3611993","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3611993","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}