InstSynth: Instance-wise Prompt-guided Style Masked Conditional Data Synthesis for Scene Understanding-Reference-Cited by-同舟云学术

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InstSynth: Instance-wise Prompt-guided Style Masked Conditional Data Synthesis for Scene Understanding

Published:2024-08-15 Issue: Volume:35 Page:1-6
ISSN:
Container-title:2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)
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Author:

Nguyen Thanh-Danh¹,Pham Bich-Nga¹,Vu Trong-Tai Dam¹,Nguyen Vinh-Tiep¹,Ngo Thanh Duc¹,Nguyen Tam V.²

Affiliation:

1. University of Information Technology,Ho Chi Minh City,Vietnam

2. University of Dayton,Dayton,OH,United States,45469

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10660665/10660652/10660775.pdf?arnumber=10660775

Reference38 articles.

1. Sora: A review on background, technology, limitations, and opportunities of large vision models;Liu,2024

2. Hierarchical text-conditional image generation with clip latents;Ramesh,2024

3. Photorealistic text-to-image diffusion models with deep language understanding;Saharia;NeurIPS,2022

4. GLIGEN: Open-Set Grounded Text-to-Image Generation

5. Gpt-4 technical report;Achiam,2023

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