LEG-SLAM: Real-Time Language-Enhanced Gaussian Splatting for SLAM

• URL: http://arxiv.org/abs/2506.03073v1
• Date: Tue, 03 Jun 2025 16:51:59 GMT
• Title: LEG-SLAM: Real-Time Language-Enhanced Gaussian Splatting for SLAM
• Authors: Roman Titkov, Egor Zubkov, Dmitry Yudin, Jaafar Mahmoud, Malik Mohrat, Gennady Sidorov,
• Abstract summary: LEG-SLAM is a novel approach that fuses an optimized Gaussian Splatting implementation with visual-language feature extraction.<n>Our method simultaneously generates high-quality photorealistic images and semantically labeled scene maps.<n>With its potential applications in autonomous robotics, augmented reality, and other interactive domains, LEG-SLAM represents a significant step forward in real-time semantic 3D Gaussian-based SLAM.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modern Gaussian Splatting methods have proven highly effective for real-time photorealistic rendering of 3D scenes. However, integrating semantic information into this representation remains a significant challenge, especially in maintaining real-time performance for SLAM (Simultaneous Localization and Mapping) applications. In this work, we introduce LEG-SLAM -- a novel approach that fuses an optimized Gaussian Splatting implementation with visual-language feature extraction using DINOv2 followed by a learnable feature compressor based on Principal Component Analysis, while enabling an online dense SLAM. Our method simultaneously generates high-quality photorealistic images and semantically labeled scene maps, achieving real-time scene reconstruction with more than 10 fps on the Replica dataset and 18 fps on ScanNet. Experimental results show that our approach significantly outperforms state-of-the-art methods in reconstruction speed while achieving competitive rendering quality. The proposed system eliminates the need for prior data preparation such as camera's ego motion or pre-computed static semantic maps. With its potential applications in autonomous robotics, augmented reality, and other interactive domains, LEG-SLAM represents a significant step forward in real-time semantic 3D Gaussian-based SLAM. Project page: https://titrom025.github.io/LEG-SLAM/

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