Diffusion-Geo: A Two-Stage Controllable Text-To-Image Generative Model for Remote Sensing Scenarios-Reference-Cited by-同舟云学术

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Diffusion-Geo: A Two-Stage Controllable Text-To-Image Generative Model for Remote Sensing Scenarios

Published:2024-07-07 Issue: Volume: Page:7003-7006
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Cai Miaoxin¹,Zhang Wei²,Zhang Tong¹,Zhuang Yin¹,Chen He¹,Chen Liang¹,Li Can¹

Affiliation:

1. Beijing Institute of Technology,National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing,Beijing,China,100081

2. Beijing Institute of Technology,Advanced Research Institute of Multidisciplinary Sciences,Beijing,China,100081

Funder

National Natural Science Foundation of China

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641523.pdf?arnumber=10641523

Reference8 articles.

1. Txt2Img-MHN: Remote Sensing Image Generation From Text Using Modern Hopfield Networks

2. DBSAGAN: Dual Branch Split Attention Generative Adversarial Network for Super-Resolution Reconstruction in Remote Sensing Images

3. Sphinx: The joint mixing of weights, tasks, and visual embeddings for multi-modal large language models;Lin,2023

4. Qwen-vl: A frontier large vision-language model with versatile abilities;Bai,2023

5. Adding Conditional Control to Text-to-Image Diffusion Models

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