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GIFStream: 4D Gaussian-based Immersive Video with Feature Stream

About

Immersive video offers a 6-Dof-free viewing experience, potentially playing a key role in future video technology. Recently, 4D Gaussian Splatting has gained attention as an effective approach for immersive video due to its high rendering efficiency and quality, though maintaining quality with manageable storage remains challenging. To address this, we introduce GIFStream, a novel 4D Gaussian representation using a canonical space and a deformation field enhanced with time-dependent feature streams. These feature streams enable complex motion modeling and allow efficient compression by leveraging temporal correspondence and motion-aware pruning. Additionally, we incorporate both temporal and spatial compression networks for end-to-end compression. Experimental results show that GIFStream delivers high-quality immersive video at 30 Mbps, with real-time rendering and fast decoding on an RTX 4090. Project page: https://xdimlab.github.io/GIFStream

Hao Li, Sicheng Li, Xiang Gao, Abudouaihati Batuer, Lu Yu, Yiyi Liao• 2025

Related benchmarks

TaskDatasetResultRank
Dynamic Scene ReconstructionN3DV (test)
PSNR31.75
32
Dynamic 3D ReconstructionN3DV
PSNR (dB)31.75
16
Novel View SynthesisNeur3D
PSNR31.75
8
Novel View SynthesisPanoptic Sport basketball and boxes
PSNR29.5
7
Novel View SynthesisMPEG
PSNR30.72
6
Long-range 4D Motion ModelingSelfCapLR Yoga
PSNR (dB)22.02
6
Long-range 4D Motion ModelingSelfCapLR Corgi newly composed
PSNR (dB)19.83
6
Long-range 4D Motion ModelingSelfCapLR newly composed
PSNR (dB)19.02
6
Long-range motion modelingSelfCapLR
tOF0.539
6
Long-range 4D Motion ModelingSelfCapLR Bike1 newly composed
PSNR (dB)18.43
6
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Code

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