Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
Skill 디렉토리
AI Agent를 위한 재사용 가능한 Skill을 찾으세요.
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
검색 결과: lidar-slam
영문 디렉토리[CVPR 2025] MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
VGGT-SLAM: Dense RGB SLAM Optimized on the SL(4) Manifold
ROS 2 LiDAR SLAM for pointcloud-map authoring, benchmarking, and Autoware-compatible map workflows.
GenZ-ICP: SOTA robust LiDAR odometry (IEEE RA-L 2025)
A Robust Approach for LiDAR-Inertial Odometry Without Sensor-Specific Modelling
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM (CVPR 2024)
[CVPR'24 Highlight & Best Demo Award] Gaussian Splatting SLAM
An open framework to simulate and deploy perception-based PX4/ArduPilot drone swarms with ROS2, YOLO, LiDAR, NVIDIA Jetson
A Comprehensive Framework for Visual SLAM Systems and Datasets
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
📖[IEEE Sensors Journal (JSEN) ] SuperVINS: A Real-Time Visual-Inertial SLAM Framework for Challenging Imaging Conditions (integrated deep learning features)