2023 IEEE Conference on Artificial Intelligence (CAI) 2023
DOI: 10.1109/cai54212.2023.00030
|View full text |Cite
|
Sign up to set email alerts
|

Synthetic Aerial Dataset for UAV Detection via Text-to-Image Diffusion Models

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 9 publications
0
2
0
Order By: Relevance
“…Additionally, image translation frameworks that combine VAE and GANs are utilized for transforming simulated images into realistic synthetic ones for training and testing change detection models [135], [137], though they still require real images for reference. Moreover, the authors in [139] introduce a method leveraging a text- • Effective for image superresolution.…”
Section: B Environmental Perceptionmentioning
confidence: 99%
See 1 more Smart Citation
“…Additionally, image translation frameworks that combine VAE and GANs are utilized for transforming simulated images into realistic synthetic ones for training and testing change detection models [135], [137], though they still require real images for reference. Moreover, the authors in [139] introduce a method leveraging a text- • Effective for image superresolution.…”
Section: B Environmental Perceptionmentioning
confidence: 99%
“…• Computationally expensive and slow to train. [139] Conditional GDM are deployed to generates photo-realistic images and corresponding ground truth bounding boxes for UAV detection according to conditional inputs, such as binary masks that specify the details and background of the UAVs, and text prompts that describe the scenes.…”
Section: Vae [133]mentioning
confidence: 99%