Immersive VR applications demand high resolutions and refresh rates, posing significant challenges for real-time rendering. Foveated rendering mitigates this cost by exploiting properties of the Human Visual System (HVS), but conventional approaches often rely on oversimplified heuristic models that neglect high-level attentional cues, resulting in artifacts in peripheral regions. To this end, we present a neural saliency-driven foveated ray tracing framework that overcomes these limitations. Our method introduces a motion-aware foveation model to capture temporal dynamics and employs a lightweight convolutional neural network to predict saliency maps that reflect complex attentional patterns derived from eye-gaze data. The combination of these guides adaptive path tracing and filtering, enabling perceptually optimized rendering with minimal artifacts. Experimental results show that our approach improves perceptual quality over prior methods while sustaining real-time performance.

Abstract The generation, processing, and measurement of microwave signals using optoelectronic technology on compact chips represent a significant trend in the evolution of microwave photonics (MWP). Among various platforms, silicon photonics has emerged as a leading choice, primarily due to its compatibility with established complementary metal-oxide-semiconductor (CMOS) processes. This compatibility enables the complete integration of high-performance radio frequency (RF) links while addressing key challenges such as size, power consumption, cost, and reliability. In this article, we review recent advancements in silicon-integrated microwave photonics, focusing on the developments of device-level integration and system-level applications. At the device level, we highlight critical innovations in silicon-based passive and active components towards MWP concerns, including ultralow-loss waveguides, high-fitness micro rings, large-bandwidth/high-linearity electro-optic modulators, hybrid/heterogeneous integrated lasers and amplifiers on silicon, frequency combs, and more. These breakthroughs form the basic foundation for advancing MWP system-level implementation. At the system-level applications, we concentrate on integrated MWP systems with diverse functionalities on silicon chips, including microwave signal generation, processing, programmable circuits, and measurement systems. Finally, we discuss current challenges and provide insights into the future of silicon-integrated MWP.

Foveated rendering reduces computational load by distributing resources based on the human visual system. This enables the implementation of ray tracing in virtual reality applications, where a high frame rate is essential to achieve visual immersion. However, traditional foveation methods based solely on eccentricity cannot adequately account for the complex behavior of visual attention. This is one of the main reasons that leads to lower perceived quality compared to non-foveated techniques. In this study, we introduce a novel rendering pipeline that incorporates ocular attention through the use of visual saliency. Based on foveation saliency, our approach facilitates the real-time production of high-quality images utilizing path tracing by distributing samples according to saliency metrics derived from geometric and historical data. To further augment image quality, an adaptive filtering process, aligned with the saliency metrics, is employed to reduce visible artifacts in non-foveal regions. Our experiments prove that this novel approach can demonstrate superior performance compared to previous methods, both in terms of quantitative metrics and perceived visual quality.