FLEXA: A Modular and Flexible Framework for AI-Assisted Video Communication - Vivot, Elton; Teixeira, Isabela; Cardoso, Kleber Vieira (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia); 2025: Proceedings of the 31st Brazilian Symposium on Multimedia and the Web, 2025)
Semantic communication offers a promising paradigm for efficient video transmission. However, existing implementations often rely on specialized, tightly coupled architectures that hinder the integration and comparative evaluation of new Artificial Intelligence (AI) models. In this paper, we present FLEXA, a modular framework for AI-assisted video communication that decouples AI processing from transport logic, enabling simplified integration of new models within a standard Web Real-Time Communication (WebRTC) environment. The architecture introduces policy-driven semantic orchestrators that dynamically manage and chain AI models during transmission. To demonstrate its capabilities, we integrated a Super-Resolution Generative Adversarial Network (SRGAN) and evaluated seven upscaling configurations under different operating policies. Results indicate that one configuration achieves the best balance between perceptual quality and efficiency, with LPIPS < 0.1 and SSIM > 0.7 under moderate processing cost. These findings demonstrate that FLEXA effectively manages different AI-driven policies, revealing an optimal operating point for resolution enhancement and quantifying the distinct performance trade-offs between different operating policies.