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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

MR-NET: Exploiting Mutual Relation for Visual Relationship Detection

February 1, 2023

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Authors

Yi Bin

University of Electronic Science and Technology of China


Yang Yang

University of Electronic Science and Technology of China


Chaofan Tao

University of Electronic Science and Technology of China


Zi Huang

University of Queensland


Jingjing Li

University of Electronic Science and Technology of China


Heng Tao Shen

University of Electronic Science and Technology of China


DOI:

10.1609/aaai.v33i01.33018110


Abstract:

Inferring the interactions between objects, a.k.a visual relationship detection, is a crucial point for vision understanding, which captures more definite concepts than object detection. Most previous work that treats the interaction between a pair of objects as a one way fail to exploit the mutual relation between objects, which is essential to modern visual application. In this work, we propose a mutual relation net, dubbed MR-Net, to explore the mutual relation between paired objects for visual relationship detection. Specifically, we construct a mutual relation space to model the mutual interaction of paired objects, and employ linear constraint to optimize the mutual interaction, which is called mutual relation learning. Our mutual relation learning does not introduce any parameters, and can adapt to improve the performance of other methods. In addition, we devise a semantic ranking loss to discriminatively penalize predicates with semantic similarity, which is ignored by traditional loss function (e.g., cross entropy with softmax). Then, our MR-Net optimizes the mutual relation learning together with semantic ranking loss with a siamese network. The experimental results on two commonly used datasets (VG and VRD) demonstrate the superior performance of the proposed approach.

Topics: AAAI

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HOW TO CITE:

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen MR-NET: Exploiting Mutual Relation for Visual Relationship Detection Proceedings of the AAAI Conference on Artificial Intelligence (2019) 8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen MR-NET: Exploiting Mutual Relation for Visual Relationship Detection AAAI 2019, 8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen (2019). MR-NET: Exploiting Mutual Relation for Visual Relationship Detection. Proceedings of the AAAI Conference on Artificial Intelligence, 8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. MR-NET: Exploiting Mutual Relation for Visual Relationship Detection. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. 2019. MR-NET: Exploiting Mutual Relation for Visual Relationship Detection. "Proceedings of the AAAI Conference on Artificial Intelligence". 8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. (2019) "MR-NET: Exploiting Mutual Relation for Visual Relationship Detection", Proceedings of the AAAI Conference on Artificial Intelligence, p.8110-8117

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen, "MR-NET: Exploiting Mutual Relation for Visual Relationship Detection", AAAI, p.8110-8117, 2019.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. "MR-NET: Exploiting Mutual Relation for Visual Relationship Detection". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. "MR-NET: Exploiting Mutual Relation for Visual Relationship Detection". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 8110-8117.

Yi Bin||Yang Yang||Chaofan Tao||Zi Huang||Jingjing Li||Heng Tao Shen. MR-NET: Exploiting Mutual Relation for Visual Relationship Detection. AAAI[Internet]. 2019[cited 2023]; 8110-8117.


ISSN: 2374-3468


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