Application Research of Virtual Reality Technology in Immersive Spatial Experience Design

This research presents an integrated framework for virtual reality spatial experience that addresses the critical challenge of achieving high visual quality while maintaining real-time performance in immersive environments. The proposed system combines transformer-based spatial generation with adaptive rendering strategies to overcome the limitations of existing approaches that treat spatial generation, rendering optimization, and user interaction as separate problems. The architecture employs a multi-scale feature extraction network with spatial attention mechanisms, integrated with foveated rendering and variable rate shading techniques for efficient resource allocation. Experimental testing on Matterport3D and Replica datasets shows dramatic improvements across all performance metrics. The system maintains stable 90 FPS rates with sub-15ms latency, a 180-times reduction from conventional NeRF methods. Visual quality assessments report PSNR of 33.5 dB and SSIM of 0.952 with the memory footprint at a stable 5.6 GB and GPU utilization at 60%. The temporal stability analysis reports consistency values of more than 0.93 across test sequences at all times, reducing quality variation that causes motion sickness to near zero. The method presented successfully balances the efficiency of computation with perceptual quality and is deployable on consumer hardware while covering applications in architectural visualization, medical simulation, and online collaboration.