2 个仓库
Awesome GitHub RepositoriesSemantic Mapping Integrations
Fusion of deep learning inference with geometric maps to assign semantic labels to 3D environments.
Distinct from Geometric Deep Learning Frameworks: Specifically addresses the fusion of semantic labels with geometric mapping, whereas the parent covers general non-Euclidean DL frameworks.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Semantic Mapping Integrations. Refine with filters or upvote what's useful.
Awesome Semantic Mapping Integrations GitHub Repositories
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- manycore-research/spatiallm
manycore-research/SpatialLM
4,596在 GitHub 上查看SpatialLM 是一个空间建模框架，利用大语言模型将单目视频和传感器数据转换为结构化的室内语义地图。它作为一个室内布局估计系统和点云语义解析器，将原始几何数据转换为建筑元素和对象类别的表示。 该项目将多模态传感器输入与语言标记对齐，使语言模型能够作为推理引擎来推断房间拓扑结构。它采用多种机制将 3D 点云和 2D 图像序列转换为离散标记和结构化空间编码，然后解码为建筑布局。 该框架涵盖 3D 场景分析和对象检测，通过边界框和语义标签识别家具。它还为机器人环境理解提供工具，处理传感器数据以创建用于自主导航的语义地图。
Fuses deep learning inference with geometric maps to assign semantic labels to architectural elements.
Pythonmllmpoint-cloudsscene-understanding - slam-handbook-contributors/slam-handbook-public-release
SLAM-Handbook-contributors/slam-handbook-public-release
4,288在 GitHub 上查看This project is a technical reference guide and sensor-based robotics manual focused on the theoretical foundations and practical implementation of Simultaneous Localization and Mapping. It serves as a knowledge base for spatial AI, covering the integration of deep learning and semantic rendering to create intelligent systems for open world environments. The resource provides guidance on integrating multi-modal sensor data from cameras, LiDAR, radar, and inertial sensors for localization and mapping. It also establishes a bibliographic standard for robotics research by providing systems for m
Integrates deep learning inference with geometric mapping to assign meaningful semantic labels to 3D spatial environments.
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