Improving Predicate Representation in Scene Graph Generation by Self-Supervised Learning-Reference-Cited by-同舟云学术

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Improving Predicate Representation in Scene Graph Generation by Self-Supervised Learning

Published:2023-01 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Hasegawa So¹,Hiromoto Masayuki¹,Nakagawa Akira¹,Umeda Yuhei¹

Affiliation:

1. Fujitsu Limited,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030744.pdf?arnumber=10030744

Reference48 articles.

1. From General to Specific: Informative Scene Graph Generation via Balance Adjustment

2. Scene Graph Generation by Iterative Message Passing

3. Bootstrap your own latent – a new approach to self-supervised learning;grill;NeurIPS,2020

4. Attention is all you need;vaswani;NeurIPS,2017

5. Scene graph reasoning for visual question answering;hildebrandt;arXiv 2007 01072,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Self-Supervised Relation Alignment for Scene Graph Generation;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

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