Research on image generation based on VAE and CGAN fusion model

Lingui Huang; Huiying Li

doi:10.1117/12.2681217

8 June 2023 Research on image generation based on VAE and CGAN fusion model

Lingui Huang, Huiying Li

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127070T (2023) https://doi.org/10.1117/12.2681217
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

The current image generation research is in full swing, and various image generation technologies emerge in endlessly. Deep learning technology has attracted wide attention since it was proposed. Research on image generation based on deep learning, such as autoencoder network, variational autoencoder network, and generation. Adversarial networks occupy an important position in the field of image generation. However, the generated image effect of each individual image generation network is not ideal. In order to generate clear images, this paper combines VAE (Variational Autoencoder Network) and CGAN (Conditional Generative Adversarial Network) to generate high-quality images. This fusion model has both the advantages of VAE network stability and CGAN network clarity. The experimental results prove that the method in this paper can achieve clear and high-quality images.

Citation Download Citation

Lingui Huang and Huiying Li "Research on image generation based on VAE and CGAN fusion model", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127070T (8 June 2023); https://doi.org/10.1117/12.2681217

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KEYWORDS

Image fusion

Gallium nitride

Data modeling

Education and training

Digital imaging

Image processing

Statistical analysis

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