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StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset | |
2023 | |
会议录名称 | IJCAI INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE |
ISSN | 1045-0823 |
卷号 | 2023-August |
页码 | 902-910 |
发表状态 | 已发表 |
摘要 | Modeling and capturing the 3D spatial arrangement of the human and the object is the key to perceiving 3D human-object interaction from monocular images. In this work, we propose to use the Human-Object Offset between anchors which are densely sampled from the surface of human mesh and object mesh to represent human-object spatial relation. Compared with previous works which use contact map or implicit distance filed to encode 3D human-object spatial relations, our method is a simple and efficient way to encode the highly detailed spatial correlation between the human and object. Based on this representation, we propose Stacked Normalizing Flow (StackFLOW) to infer the posterior distribution of human-object spatial relations from the image. During the optimization stage, we finetune the human body pose and object 6D pose by maximizing the likelihood of samples based on this posterior distribution and minimizing the 2D-3D corresponding reprojection loss. Extensive experimental results show that our method achieves impressive results on two challenging benchmarks, BEHAVE and InterCap datasets. Our code has been publicly available at https://github.com/huochf/StackFLOW. © 2023 International Joint Conferences on Artificial Intelligence. All rights reserved. |
会议录编者/会议主办者 | International Joint Conferences on Artifical Intelligence (IJCAI) |
关键词 | Artificial intelligence Mesh generation Contacts map Human-object interaction Monocular image Object reconstruction Optimisations Posterior distributions Simple++ Spatial arrangements Spatial correlations Spatial relations |
会议名称 | 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 |
会议地点 | Macao, China |
会议日期 | August 19, 2023 - August 25, 2023 |
收录类别 | EI |
语种 | 英语 |
出版者 | International Joint Conferences on Artificial Intelligence |
EI入藏号 | 20233714713485 |
EI主题词 | Encoding (symbols) |
EI分类号 | 723.2 Data Processing and Image Processing ; 723.4 Artificial Intelligence ; 723.5 Computer Applications ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory |
原始文献类型 | Conference article (CA) |
文献类型 | 会议论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/348727 |
专题 | 信息科学与技术学院_硕士生 信息科学与技术学院_PI研究组_虞晶怡组 信息科学与技术学院_PI研究组_许岚组 信息科学与技术学院_PI研究组_马月昕 信息科学与技术学院_PI研究组_汪婧雅组 信息科学与技术学院_PI研究组_石野组 |
通讯作者 | Wang, Jingya |
作者单位 | 1.ShanghaiTech University, China 2.Shanghai Engineering Research Center of Intelligent Vision and Imaging, China |
第一作者单位 | 上海科技大学 |
通讯作者单位 | 上海科技大学 |
第一作者的第一单位 | 上海科技大学 |
推荐引用方式 GB/T 7714 | Huo, Chaofan,Shi, Ye,Ma, Yuexin,et al. StackFLOW: Monocular Human-Object Reconstruction by Stacked Normalizing Flow with Offset[C]//International Joint Conferences on Artifical Intelligence (IJCAI):International Joint Conferences on Artificial Intelligence,2023:902-910. |
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