PD-4DGS:Progressive Decomposition of 4D Gaussian Splatting for Bandwidth-Adaptive Dynamic Scene Streaming
Jiachen Li, Guangzhi Han, Jin Wan, Delong Han, Yuan Gao, Min Li, Mingle Zhou, Gang Li

TL;DR
PD-4DGS introduces a hierarchical, progressive compression framework for 4D Gaussian Splatting, enabling scalable, on-demand streaming with significantly reduced latency and bandwidth requirements.
Contribution
It is the first to enable progressive compression and on-demand transmission of 4D Gaussian Splatting for dynamic scene streaming.
Findings
Reduces streamed bitstream size by over 60% at same fidelity.
Decreases first-frame latency from up to 930 seconds to about 1.7 seconds on a 2 Mbps link.
Enables true on-demand progressive streaming for 4D Gaussian Splatting.
Abstract
4D Gaussian Splatting (4DGS) enables high-quality dynamic novel view synthesis, yet current models remain monolithic bitstreams that clients must download in full before any frame can be rendered, causing black-screen waits of tens to hundreds of seconds on mobile bandwidth and leaving 4DGS incompatible with modern adaptive-bitrate delivery. Progressive 3DGS compression alleviates this for static scenes, but it acts only on spatial anchors and cannot partition the temporal deformation networks that dominate dynamic-scene size. We present PD-4DGS, the first framework for progressive compression and on-demand transmission of 4DGS. Hierarchical Deformation Decomposition (HDD) externalises the coarse-to-fine motion hierarchy already latent in 4DGS into three independently transmittable layers -- a static scaffold, a global deformation, and a local refinement -- so that any prefix of the…
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