Improving Real-time 3D Reconstruction and Semantic Segmentation for AR Applications

This paper presents an innovative approach to enhancing real-time 3D reconstruction and semantic segmentation for Augmented Reality (AR) applications using advanced Artificial Intelligence (AI) techniques. We introduce a novel hybrid architecture that combines a lightweight NeRF (Neural Radiance Fields) variant with a real-time semantic segmentation network. Our method achieves state-of-the-art performance in both 3D reconstruction accuracy and semantic understanding while maintaining real-time performance on mobile AR devices. Experimental results demonstrate significant improvements in reconstruction quality, segmentation accuracy, and computational efficiency compared to existing methods.