AirGS: Real-Time 4D Gaussian Streaming for Free-Viewpoint Video Experiences
Zhe Wang, Jinghang Li, Yifei Zhu

TL;DR
AirGS is a streaming-optimized 4D Gaussian Splatting framework that enhances free-viewpoint video quality and efficiency by improving training, transmission, and reconstruction processes for real-time immersive experiences.
Contribution
It introduces a novel streaming pipeline, keyframe enhancement, and adaptive pruning algorithms to improve 4DGS quality and reduce bandwidth in free-viewpoint videos.
Findings
Reduces PSNR quality deviation by over 20% during scene changes.
Maintains frame PSNR above 30 consistently.
Speeds up training by 6 times and halves transmission size.
Abstract
Free-viewpoint video (FVV) enables immersive viewing experiences by allowing users to view scenes from arbitrary perspectives. As a prominent reconstruction technique for FVV generation, 4D Gaussian Splatting (4DGS) models dynamic scenes with time-varying 3D Gaussian ellipsoids and achieves high-quality rendering via fast rasterization. However, existing 4DGS approaches suffer from quality degradation over long sequences and impose substantial bandwidth and storage overhead, limiting their applicability in real-time and wide-scale deployments. Therefore, we present AirGS, a streaming-optimized 4DGS framework that rearchitects the training and delivery pipeline to enable high-quality, low-latency FVV experiences. AirGS converts Gaussian video streams into multi-channel 2D formats and intelligently identifies keyframes to enhance frame reconstruction quality. It further combines temporal…
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Taxonomy
TopicsVideo Coding and Compression Technologies · Advanced Vision and Imaging · Image and Video Quality Assessment
