GIFStream: 4D Gaussian-based Immersive Video with Feature Stream
Hao Li, Sicheng Li, Xiang Gao, Abudouaihati Batuer, Lu Yu, Yiyi Liao
Abstract
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 their motion-awareness and temporal correspondence. 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.
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Cited by top-tier papers6
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- SmoothMotionVectors: Optimizing Your Content for Video Codecs in Free View Video CompressionMingyang Song, Yang Zhang, Siyu Tang, Tunç Ozan AydinSIGGRAPH 2026
- StreamSTGS: Streaming Spatial and Temporal Gaussian Grids for Real-Time Free-Viewpoint VideoZhihui Ke, Yuyang Liu, Xiaobo Zhou, Tie QiuAAAI 2026
- CAGS: Color-Adaptive Volumetric Video Streaming with Dynamic 3D Gaussian SplattingDaheng Yin, Yili Jin, Jianxin Shi, Isaac Ding et al.SIGGRAPH 2026
Builds on24
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- LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPSZhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu et al.NeurIPS 2024 · 681 citations
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- Deep Contextual Video CompressionJiahao Li, Bin Li, Yan LuNeurIPS 2021 · 518 citations
- 4D Gaussian Splatting for Real-Time Dynamic Scene RenderingGuanjun Wu, Taoran Yi, Jiemin Fang, Lingxi Xie et al.CVPR 2024 · 513 citations
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