Learning from Easy to Hard Pairs: Multi-step Reasoning Network for Human-Object Interaction Detection

Author:

Zhou Yuchen1ORCID,Tan Guang1ORCID,Li Mengtang1ORCID,Gou Chao1ORCID

Affiliation:

1. School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China

Funder

Natural Science Foundation of Guangdong Province

Shenzhen Basic Research Fund

Publisher

ACM

Reference48 articles.

1. End-to-End Object Detection with Transformers

2. Yu-Wei Chao , Yunfan Liu , Xieyang Liu , Huayi Zeng , and Jia Deng . 2018. Learning to detect human-object interactions. In 2018 ieee winter conference on applications of computer vision (wacv) . IEEE , 381--389. Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, and Jia Deng. 2018. Learning to detect human-object interactions. In 2018 ieee winter conference on applications of computer vision (wacv). IEEE, 381--389.

3. Reformulating HOI Detection as Adaptive Set Prediction

4. Category-Aware Transformer Network for Better Human-Object Interaction Detection

5. Chen Gao , Jiarui Xu , Yuliang Zou , and Jia-Bin Huang . 2020 . Drg: Dual relation graph for human-object interaction detection. In Computer Vision-ECCV 2020: 16th European Conference , Glasgow, UK , August 23-28, 2020, Proceedings, Part XII 16. Springer , 696--712. Chen Gao, Jiarui Xu, Yuliang Zou, and Jia-Bin Huang. 2020. Drg: Dual relation graph for human-object interaction detection. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XII 16. Springer, 696--712.

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