Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects

Automatic scene generation is an essential area of research with applications in robotics, recreation, visual representation, training and simulation, education, and more. This survey provides a comprehensive review of the current state-of-the-arts in automatic scene generation, focusing on techniqu...

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Detalles Bibliográficos

Principais autores:	Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2025-01-01
Series:	IEEE Access
Assuntos:	Automatic scene generation variational autoencoders generative adversarial networks transformers diffusion models machine learning
Acceso en liña:	https://ieeexplore.ieee.org/document/11016674/
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