Building and Optimizing Lightweight Generative Adversarial Neural Networks to Enhance Video Quality in the Client Devices Using Webgpu
The paper considers problems for the tasks of improving the quality of digital video images for cloud environments, as well as on the client side using generative adversarial neural networks (GANs) adapted for work in the browser. A method is proposed that uses WebGPU for accelerated execution of convolutional calculations, which allows to increase the resolution and improve the quality of low-quality video in real time without significant load on servers.