Image Generative Adversarial Networks (GANs) have revolutionized the field of computer vision by enabling the generation of realistic and high-quality images. GANs consist of two neural networks: a generator network that synthesizes images, and a discriminator network that tries to distinguish real images from the generated ones. The generator and discriminator are trained in an adversarial manner, leading to the generation of highly realistic images.
The widespread adoption of mobile devices, such as smartphones and tablets, has made them an essential part of our daily lives. These devices possess considerable computational power, making them potential candidates for deploying computationally intensive tasks like GANs. Deploying GANs on mobile devices opens up a range of possibilities, including on-device image generation, augmented reality applications, and personalized content generation. Challenges of GAN Deployment on Mobile Devices While deploying GANs on mobile devices offers exciting opportunities, several challenges need to be addressed for successful implementation.