Method | Score | Submission Time | Contributors | Description |
---|---|---|---|---|
URNet | 0.6604 | Oct. 17, 2019, 9:08 p.m. | Tianfei Zhou, Wenguan Wang, Jianbing Shen, Zhijie Zhang (Inception Institute of Artificial Intelligence) | We propose a Unified Relationship detection Network (URNet) in this contest. We jointly train entity detection/segmentation and relationship inference in an end-to-end way. Our URNet is built on Cascade (Mask)RCNN, which is further extended to add a new branch for relationship recognition for each human-object pair. The relationship recognition branch operates on rich multi-modal features for accurate inference. |
GMVM | 0.6026 | Oct. 17, 2019, 5:11 a.m. | Zanhui Fan, Han Wang, Peng Chen, Yusen Qin, Shengjin Wang, Zichong Chen (Segway Robotics, Tsinghua University, Dalian Neusoft University of Information) | The interactions in HOI-W challenge are highly correlated with object categories and location information is critical to determining whether an interaction between a person and an object exists. We propose a human-object-interaction detection scheme consisting of three parts… |
Faster Interaction Net | 0.5693 | Oct. 17, 2019, 5:01 a.m. | Haoliang Tan, Yu Zhu, Guodong Guo (Institute of Deep Learning, Baidu Research, Xi’an Jiaotong University, Xi’an, China, National Engineering Laboratory for Deep Learning Technology and Application, Beijing China) | We decompose the problem into two steps: 1) Human and Object bounding-boxes detection and 2) human-object Interaction recognition… |
F2INet | 0.4913 | Oct. 17, 2019, 5:06 a.m. | Shuchang Lyu, Lingyun Zeng (Beihang University) | We propose a two-stage architecture named Faster Fusion Interaction Network (F2INet) for the human-object interaction (HOI) task… |
test | 0.4871 | Oct. 17, 2019, 8:43 p.m. | test | test |
m15_9 | 0.4477 | Oct. 17, 2019, 9:53 p.m. | 9 | 9 |
6_post | 0.4268 | Oct. 17, 2019, 9:24 p.m. | 6 | 6 |
Hierarchical joint training model | 0.4114 | Oct. 17, 2019, 5:08 a.m. | Xijie Huang, Yong-Lu Li, Xinpeng Liu (Shanghai Jiao Tong University) | We apply a hierarchical joint training scheme… |
FNet | 0.3965 | Oct. 17, 2019, 2:18 p.m. | changge | fusion model |
geometry embedding baseline | 0.3292 | Oct. 17, 2019, 5:09 a.m. | Rongjie Li, Haozhe Wang (ShanghaiaTech University, China) | We resampled the detection boxes while training and added a module which embedding the relvant position of subject and object for encoded the geometry information. |
zsp | 0.204 | Oct. 17, 2019, 5:26 a.m. | – | – |
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