論文紹介：Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
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The document presents a retrieval-augmented layout transformer designed for content-aware layout generation, highlighting its integration with various generation techniques and models. It discusses components such as the retrieval augmentation module and layout decoder, along with performance metrics to evaluate its effectiveness. The system aims to enhance the quality of generated layouts, leveraging recent advancements in generative models.
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BB
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→ (RAG)
[Donovan+, CHI2015]
Retrieval-Augmented Generation](https://image.slidesharecdn.com/20240530retrieval-augmentedlayouttransformerforcontent-awarelayoutgeneration-240604091605-60b455c8/85/Retrieval-Augmented-Layout-Transformer-for-Content-Aware-Layout-Generation-2-320.jpg)
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[Yang+, ACM TOMM2016]
• NN [Li+, ICLR2019] [Arroyo+,
CVPR2021]
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• GAN
• VAE
• Diffusion Model
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• ContentGAN [Zheng+, ACM TOG2019]
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• CGLGAN [Zhou+, IJCAI2022]
•](https://image.slidesharecdn.com/20240530retrieval-augmentedlayouttransformerforcontent-awarelayoutgeneration-240604091605-60b455c8/85/Retrieval-Augmented-Layout-Transformer-for-Content-Aware-Layout-Generation-4-320.jpg)
![Image encoder
CGL-GAN [Zhou+, CVPR2022]](https://image.slidesharecdn.com/20240530retrieval-augmentedlayouttransformerforcontent-awarelayoutgeneration-240604091605-60b455c8/85/Retrieval-Augmented-Layout-Transformer-for-Content-Aware-Layout-Generation-11-320.jpg)
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• CGL [Zhou+, IJCAI2022]
• 60,548
• 1,000
• 100
• PKU [Hsu+, CVPR2023]
• 9,974
• 905
• 100
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• FID↓
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• Occ↓
• Rea↓
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• K K=16
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• 350, 240](https://image.slidesharecdn.com/20240530retrieval-augmentedlayouttransformerforcontent-awarelayoutgeneration-240604091605-60b455c8/85/Retrieval-Augmented-Layout-Transformer-for-Content-Aware-Layout-Generation-15-320.jpg)
論文紹介：Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
- 1. Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation Daichi Horita, Naoto Inoue, Kotaro Kikuchi, Kota Yamaguchi, Kiyoharu Aizawa, CVPR2024 2024/05/30
- 3. Retrieval-Augmented Generation n RAG • (LLM) • • LLM • n • • RAG
- 4. n • [Yang+, ACM TOMM2016] • NN [Li+, ICLR2019] [Arroyo+, CVPR2021] • • GAN • VAE • Diffusion Model n • ContentGAN [Zheng+, ACM TOG2019] • • CGLGAN [Zhou+, IJCAI2022] •
- 11. Image encoder CGL-GAN [Zhou+, CVPR2022]
- 15. n • • CGL [Zhou+, IJCAI2022] • 60,548 • 1,000 • 100 • PKU [Hsu+, CVPR2023] • 9,974 • 905 • 100 n • • FID↓ • (Und↓) • (Ove↓) • • Occ↓ • Rea↓ n • K K=16 • • 350, 240
- 16. n
- 17. n
- 22. C : S : P :