Mobile-4DGS: Unified Static-Dynamic Real-time Mobile Gaussian Splatting
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Abstract (arXiv)
Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable performance in novel view synthesis, yet deploying both static and dynamic Gaussian representations on resource-constrained mobile devices remains challenging due to heavy storage, redundant primitives, and costly per-frame computation. We present Mobile-4DGS, a unified lightweight framework for high-fidelity real-time static and dynamic Gaussian rendering on mobile platforms. For compact appearance modeling, we introduce a Monte Carlo Specular Energy Aggregator that compresses high-order radiance residuals into the first-order Spherical Harmonics (SH), together with an Attribute-Conditioned SH Enhancement module whose predicted offsets are pre-baked before inference. We further propose a Multi-View Alpha-Based Densification and Pruning strategy to suppress redundant primitives while maintaining multi-view consistency. For dynamic scenes, we develop a compact explicit 4D representation by constructing second-order Gaussian motion, learnable temporal support, and a binary static-dynamic partition, enabling continuous-time modeling without runtime deformation networks. Based on this partition, a Depth-Order Certificate selectively reuses previously committed depth orders to reduce re-projection, sorting, merging, and index-buffer updates during playback. Extensive experiments on static and dynamic scenes demonstrate that Mobile-4DGS substantially reduces storage and rendering overhead while maintaining competitive visual quality, enabling real-time 3D and 4D Gaussian Splatting on mobile devices. textcolormagentahrefhttps://xiaobiaodu.github.io/mobile-4dgs-project/Code has been released: https://xiaobiaodu.github.io/mobile-4dgs-project/.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 73 of its 89 references that are in the map. First posted on arXiv 4 Oct 2026.
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References · 73
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
- 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
- 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,157
- 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
- 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 861
- 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
- 2023Scaffold-GS: Structured 3D Gaussians for View-Adaptive Renderingcited by 695
- 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 689
- 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 600
- 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
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- 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 560
- 2023Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splattingcited by 476
- 2021Baking Neural Radiance Fields for Real-Time View Synthesiscited by 468
- 2023LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPScited by 436
- 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 405
- 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 372
- 2023SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenescited by 347
- 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 311
- 2019Differentiable Surface Splatting for Point-based Geometry Processingcited by 239
- 2024Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussianscited by 230
- 20243D Gaussian Splatting as Markov Chain Monte Carlocited by 217
- 2024Mini-Splatting: Representing Scenes with a Constrained Number of Gaussianscited by 213
- 2024HAC: Hash-grid Assisted Context for 3D Gaussian Splatting Compressioncited by 209
- 2024Taming 3DGS: High-Quality Radiance Fields with Limited Resourcescited by 204
- 2023EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingScited by 196
- 2021Point-Based Neural Rendering with Per-View Optimizationcited by 190
- 20244D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenescited by 189
- 2024VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Realitycited by 179
- 2024Reducing the Memory Footprint of 3D Gaussian Splattingcited by 133
- 2024Revising Densification in Gaussian Splattingcited by 128
- 2024RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPScited by 113
- 2024Pixel-GS: Density Control with Pixel-aware Gradient for 3D Gaussian Splattingcited by 113
- 2024StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time Renderingcited by 111
- 2024ContextGS: Compact 3D Gaussian Splatting with Anchor Level Context Modelcited by 102
- 2024PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splattingcited by 95
- 2024Speedy-Splat: Fast 3D Gaussian Splatting with Sparse Pixels and Sparse Primitivescited by 95
- 2023Anything-3D: Towards Single-view Anything Reconstruction in the Wildcited by 92
- 2024FlashGS: Efficient 3D Gaussian Splatting for Large-scale and High-resolution Renderingcited by 88
- 2023Neural Point Catacaustics for Novel-View Synthesis of Reflectionscited by 82
- 2024CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splattingcited by 82
- 2020Learning Object Relation Graph and Tentative Policy for Visual Navigationcited by 64
- 20243D Gaussian Splatting with Deferred Reflectioncited by 63
- 2025HAC++: Towards 100X Compression of 3D Gaussian Splattingcited by 57
- 2024MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformationcited by 56
- 2022MPS-NeRF: Generalizable 3D Human Rendering from Multiview Imagescited by 53
- 2021VTNet: Visual Transformer Network for Object Goal Navigationcited by 51
- 2024MEGA: Memory-Efficient 4D Gaussian Splatting for Dynamic Scenescited by 47
- 20243D-HGS: 3D Half-Gaussian Splattingcited by 44
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