GANs and AI: Shaping the Future of Computer Vision
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V3I4P103Keywords:
Computer Vision, Generative Adversarial Networks (GANs), Image Synthesis, Super-Resolution, Image-to-Image Translation, Style TransferAbstract
To date, GANs are acknowledged to be the most remarkable invention in the sphere of computer vision as they provide an opportunity to achieve breakthroughs in such areas as image enhancement, manipulation, and generation. The following paper will focus on discussing the changes GANs have introduced to computer vision and also their capacity to produce very realistic images, augment the quantity of detail and manipulate real images. While the GAN’s general description is provided in the abstract in terms of its usefulness, the specifics include its architecture where GAN concepts such as the GAN training process and the generator/discriminator. Regarding the aspect of super-resolution and image-to-image translation, the paper concentrates on the bright future of GANs for shifting the paradigms of the computer vision field. Furthermore, the problems stated in the abstract and the possible ethical concerns related to GANs are different, while reasonable usage of the concept is highly emphasized. Despite that, several improvements of GANs in future are expected to enhance other AI components’ integration, which has more directions for CV’s development and testing
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References
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