[
    {
        "id": "osp-18052",
        "type": "article-journal",
        "title": "Mobile-4DGS: Unified Static-Dynamic Real-time Mobile Gaussian Splatting",
        "author": [
            {
                "family": "Du",
                "given": "Xiaobiao"
            },
            {
                "family": "Hao",
                "given": "Beixi"
            },
            {
                "family": "Fang",
                "given": "Zhen"
            },
            {
                "family": "Zhu",
                "given": "Tianqing"
            },
            {
                "family": "Hartley",
                "given": "Richard"
            },
            {
                "family": "Yu",
                "given": "Xin"
            }
        ],
        "URL": "https://omanscience.com/en/articles/mobile-4dgs-unified-static-dynamic-real-time-mobile-gaussian-splatting",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "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. \\textcolor{magenta}{\\href{https://xiaobiaodu.github.io/mobile-4dgs-project/}{Code has been released: https://xiaobiaodu.github.io/mobile-4dgs-project/}}."
    }
]