{"id":25,"date":"2023-07-18T21:29:44","date_gmt":"2023-07-18T21:29:44","guid":{"rendered":"https:\/\/picdataset.com\/?p=25"},"modified":"2023-07-18T21:29:46","modified_gmt":"2023-07-18T21:29:46","slug":"hoi2019","status":"publish","type":"post","link":"https:\/\/picdataset.com\/challenge\/leaderboard\/hoi2019\/","title":{"rendered":"hoi2019"},"content":{"rendered":"\n
Method<\/th>Score<\/th>Submission Time<\/th>Contributors<\/th>Description<\/th><\/tr><\/thead>
URNet<\/td>0.6604<\/td>Oct. 17, 2019, 9:08 p.m.<\/td>Tianfei Zhou, Wenguan Wang, Jianbing Shen, Zhijie Zhang (Inception Institute of Artificial Intelligence<\/a>)<\/td>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.<\/td><\/tr>
GMVM<\/td>0.6026<\/td>Oct. 17, 2019, 5:11 a.m.<\/td>Zanhui Fan, Han Wang, Peng Chen, Yusen Qin, Shengjin Wang, Zichong Chen (Segway Robotics, Tsinghua University, Dalian Neusoft University of Information)<\/td>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\u2026<\/td><\/tr>
Faster Interaction Net<\/td>0.5693<\/td>Oct. 17, 2019, 5:01 a.m.<\/td>Haoliang Tan, Yu Zhu, Guodong Guo (Institute of Deep Learning, Baidu Research, Xi\u2019an Jiaotong University, Xi\u2019an, China, National Engineering Laboratory for Deep Learning Technology and Application, Beijing China)<\/td>We decompose the problem into two steps: 1) Human and Object bounding-boxes detection and 2) human-object Interaction recognition\u2026<\/td><\/tr>
F2INet<\/td>0.4913<\/td>Oct. 17, 2019, 5:06 a.m.<\/td>Shuchang Lyu, Lingyun Zeng (Beihang University)<\/td>We propose a two-stage architecture<\/a> named Faster Fusion Interaction Network (F2INet) for the human-object interaction (HOI) task\u2026<\/td><\/tr>
test<\/td>0.4871<\/td>Oct. 17, 2019, 8:43 p.m.<\/td>test<\/td>test<\/td><\/tr>
m15_9<\/td>0.4477<\/td>Oct. 17, 2019, 9:53 p.m.<\/td>9<\/td>9<\/td><\/tr>
6_post<\/td>0.4268<\/td>Oct. 17, 2019, 9:24 p.m.<\/td>6<\/td>6<\/td><\/tr>
Hierarchical joint training model<\/td>0.4114<\/td>Oct. 17, 2019, 5:08 a.m.<\/td>Xijie Huang, Yong-Lu Li, Xinpeng Liu (Shanghai Jiao Tong University)<\/td>We apply a hierarchical joint training scheme\u2026<\/td><\/tr>
FNet<\/td>0.3965<\/td>Oct. 17, 2019, 2:18 p.m.<\/td>changge<\/td>fusion model<\/td><\/tr>
geometry embedding baseline<\/td>0.3292<\/td>Oct. 17, 2019, 5:09 a.m.<\/td>Rongjie Li, Haozhe Wang (ShanghaiaTech University, China)<\/td>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.<\/td><\/tr>
zsp<\/td>0.204<\/td>Oct. 17, 2019, 5:26 a.m.<\/td>–<\/td>–<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

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 … Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[6],"tags":[],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/posts\/25"}],"collection":[{"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/comments?post=25"}],"version-history":[{"count":2,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/posts\/25\/revisions"}],"predecessor-version":[{"id":27,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/posts\/25\/revisions\/27"}],"wp:attachment":[{"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/media?parent=25"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/categories?post=25"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/picdataset.com\/wp-json\/wp\/v2\/tags?post=25"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}