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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Bibliographic Details
Main Authors:	Awal Ahmed Fime, Saifuddin Mahmud, Arpita Das, Md. Sunzidul Islam, Jong-Hoon Kim
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Automatic scene generation variational autoencoders generative adversarial networks transformers diffusion models machine learning
Online Access:	https://ieeexplore.ieee.org/document/11016674/
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Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects

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