FOVI-Dex is a proposed solution that enhances robotic reinforcement learning by utilizing foveated rendering and perception, which reduces rendering costs and improves policy training efficiency. The results show that FOVI-Dex significantly outperforms traditional high-resolution camera setups in both simulation and real-world applications, making it a promising approach for efficient dexterous manipulation learning.