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📄 Abstract
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. The data and code will be available soon.
Authors (11)
Bingchen Miao
Rong Wei
Zhiqi Ge
Xiaoquan sun
Shiqi Gao
Jingzhe Zhu
+5 more
Submitted
October 24, 2025
Key Contributions
SAGE-3D upgrades 3D Gaussian Splatting (3DGS) into an executable, semantically and physically aligned environment for embodied navigation. It introduces object-centric semantic grounding and physics-aware execution, along with the InteriorGS dataset and SAGE-Bench benchmark.
Business Value
Facilitates the development and testing of more capable navigation systems for robots and autonomous agents by providing realistic and interactive simulated environments, reducing the need for extensive real-world testing.