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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.04143 |
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| _version_ | 1866910290693586944 |
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| author | Xie, Xianghui Wang, Xi Athanasiou, Nikos Bhatnagar, Bharat Lal Huang, Chun-Hao P. Mo, Kaichun Chen, Hao Jia, Xia Zhang, Zerui Cui, Liangxian Lin, Xiao Qian, Bingqiao Xiao, Jie Yang, Wenfei Nam, Hyeongjin Jung, Daniel Sungho Kim, Kihoon Lee, Kyoung Mu Hilliges, Otmar Pons-Moll, Gerard |
| author_facet | Xie, Xianghui Wang, Xi Athanasiou, Nikos Bhatnagar, Bharat Lal Huang, Chun-Hao P. Mo, Kaichun Chen, Hao Jia, Xia Zhang, Zerui Cui, Liangxian Lin, Xiao Qian, Bingqiao Xiao, Jie Yang, Wenfei Nam, Hyeongjin Jung, Daniel Sungho Kim, Kihoon Lee, Kyoung Mu Hilliges, Otmar Pons-Moll, Gerard |
| contents | Modeling the interaction between humans and objects has been an emerging research direction in recent years. Capturing human-object interaction is however a very challenging task due to heavy occlusion and complex dynamics, which requires understanding not only 3D human pose, and object pose but also the interaction between them. Reconstruction of 3D humans and objects has been two separate research fields in computer vision for a long time. We hence proposed the first RHOBIN challenge: reconstruction of human-object interactions in conjunction with the RHOBIN workshop. It was aimed at bringing the research communities of human and object reconstruction as well as interaction modeling together to discuss techniques and exchange ideas. Our challenge consists of three tracks of 3D reconstruction from monocular RGB images with a focus on dealing with challenging interaction scenarios. Our challenge attracted more than 100 participants with more than 300 submissions, indicating the broad interest in the research communities. This paper describes the settings of our challenge and discusses the winning methods of each track in more detail. We observe that the human reconstruction task is becoming mature even under heavy occlusion settings while object pose estimation and joint reconstruction remain challenging tasks. With the growing interest in interaction modeling, we hope this report can provide useful insights and foster future research in this direction. Our workshop website can be found at \href{https://rhobin-challenge.github.io/}{https://rhobin-challenge.github.io/}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_04143 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RHOBIN Challenge: Reconstruction of Human Object Interaction Xie, Xianghui Wang, Xi Athanasiou, Nikos Bhatnagar, Bharat Lal Huang, Chun-Hao P. Mo, Kaichun Chen, Hao Jia, Xia Zhang, Zerui Cui, Liangxian Lin, Xiao Qian, Bingqiao Xiao, Jie Yang, Wenfei Nam, Hyeongjin Jung, Daniel Sungho Kim, Kihoon Lee, Kyoung Mu Hilliges, Otmar Pons-Moll, Gerard Computer Vision and Pattern Recognition Modeling the interaction between humans and objects has been an emerging research direction in recent years. Capturing human-object interaction is however a very challenging task due to heavy occlusion and complex dynamics, which requires understanding not only 3D human pose, and object pose but also the interaction between them. Reconstruction of 3D humans and objects has been two separate research fields in computer vision for a long time. We hence proposed the first RHOBIN challenge: reconstruction of human-object interactions in conjunction with the RHOBIN workshop. It was aimed at bringing the research communities of human and object reconstruction as well as interaction modeling together to discuss techniques and exchange ideas. Our challenge consists of three tracks of 3D reconstruction from monocular RGB images with a focus on dealing with challenging interaction scenarios. Our challenge attracted more than 100 participants with more than 300 submissions, indicating the broad interest in the research communities. This paper describes the settings of our challenge and discusses the winning methods of each track in more detail. We observe that the human reconstruction task is becoming mature even under heavy occlusion settings while object pose estimation and joint reconstruction remain challenging tasks. With the growing interest in interaction modeling, we hope this report can provide useful insights and foster future research in this direction. Our workshop website can be found at \href{https://rhobin-challenge.github.io/}{https://rhobin-challenge.github.io/}. |
| title | RHOBIN Challenge: Reconstruction of Human Object Interaction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2401.04143 |