{"ID":2850570,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.21307","arxiv_id":"2510.21307","title":"Towards Physically Executable 3D Gaussian for Embodied Navigation","abstract":"3D Gaussian Splatting (3DGS), a 3D representation method with photorealistic real-time rendering capabilities, is regarded as an effective tool for narrowing the sim-to-real gap. However, it lacks fine-grained semantics and physical executability for Visual-Language Navigation (VLN). To address this, we propose SAGE-3D (Semantically and Physically Aligned Gaussian Environments for 3D Navigation), a new paradigm that upgrades 3DGS into an executable, semantically and physically aligned environment. It comprises two components: (1) Object-Centric Semantic Grounding, which adds object-level fine-grained annotations to 3DGS; and (2) Physics-Aware Execution Jointing, which embeds collision objects into 3DGS and constructs rich physical interfaces. We release InteriorGS, containing 1K object-annotated 3DGS indoor scene data, and introduce SAGE-Bench, the first 3DGS-based VLN benchmark with 2M VLN data. Experiments show that 3DGS scene data is more difficult to converge, while exhibiting strong generalizability, improving baseline performance by 31% on the VLN-CE Unseen task. Our data and code are available at: https://sage-3d.github.io.","short_abstract":"3D Gaussian Splatting (3DGS), a 3D representation method with photorealistic real-time rendering capabilities, is regarded as an effective tool for narrowing the sim-to-real gap. However, it lacks fine-grained semantics and physical executability for Visual-Language Navigation (VLN). To address this, we propose SAGE-3D...","url_abs":"https://arxiv.org/abs/2510.21307","url_pdf":"https://arxiv.org/pdf/2510.21307v2","authors":"[\"Bingchen Miao\",\"Rong Wei\",\"Zhiqi Ge\",\"Xiaoquan sun\",\"Shiqi Gao\",\"Jingzhe Zhu\",\"Renhan Wang\",\"Siliang Tang\",\"Jun Xiao\",\"Rui Tang\",\"Juncheng Li\"]","published":"2025-10-24T10:05:00Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}