pyc5714

pyc5714's Stars

• CASIA-IVA-Lab/FastSAM

  Fast Segment Anything

  Language:Python7.6k56209709

• ChaoningZhang/MobileSAM

  This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!

  Language:Jupyter Notebook4.9k42125508

• HKUST-Aerial-Robotics/VINS-Fusion

  An optimization-based multi-sensor state estimator

  Language:C++3.6k1202441.4k

• utiasSTARS/pykitti

  Python tools for working with KITTI data.

  Language:Python1.2k2361242

• ethz-asl/lidar_align

  A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor

  Language:C++8833132270

• koide3/direct_visual_lidar_calibration

  A toolbox for target-less LiDAR-camera calibration [ROS1/ROS2]

  Language:C++80920118126

• hku-mars/STD

  A 3D point cloud descriptor for place recognition

  Language:C++609264072

• at-wat/mcl_3dl

  A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.

  Language:C++50725133118

• VincentCheungM/Run_based_segmentation

  An ongoing implementation ros node on `fast segmentation of 3d point clouds: a paradigm`...

  Language:C++3951123120

• ros2/rosbag2

  Language:C++29239594255

• url-kaist/TRAVEL

  Traversable ground and above-ground object segmentation using graph representation of 3D LiDAR scans

  Language:C++27551330

• HaisenbergPeng/ROLL

  A real-time, robust LiDAR-inertial localization system

  Language:C++20210826

• Navy-RISE-Lab/ground-texture-slam

  Language:C++1506327

• PRBonn/3DUIS

  Language:Python8613311

• Unsigned-Long/slam-tricks

  small, powerful and beautiful slam tricks with theory and practice

  Language:C++802112

• YZH-bot/RH-Map

  RH-Map: Online dynamic objects removal [RA-L 23]

  Language:Python751422

• preethamam/PCL-FeatureBased-PointCloudRegistration

  A computer program on PCL framework to register two point clouds using the feature-based keypoints (SIFT, SHOT, FPFH, etc.), local/global feature descriptors, followed by various correspondence estimation and rejection methods. Below summarizes the available keypoints, descriptors, correspondence estimation and rejection methods that works in different combinations.

  Language:C++64108

• HyeonJaeGil/DockerSLAM

  User-friendly Docker images for SLAM

  Language:Dockerfile37313

• Jiang-Muyun/PointNet12

  Combination of Pointnet and Pointnet++ with KITTI Point Cloud Semantic Segmentation Dataset

  Language:Python313810

• Holy-Ground/cmake_ground

  CMake example for modular systems

  Language:CMake27005

• Kin-Zhang/ERASOR

  Dynamic Map benchmark implementation

  Language:C++24005

• borongyuan/FAST_LIO

  A computationally efficient and robust LiDAR-inertial odometry (LIO) package

  Language:C++17102

• mit-acl/fastsam_ros

  ROS wrapper for FastSAM, with docker

  Language:Python17201

• dfki-ric/pclomp

  Multi-threaded and SSE friendly NDT algorithm

  Language:C++16000

• crystaldust/lio_sam_ros2

  A ros2 version of LIO-SAM

  Language:C++10105

• Kyungpyo-Kim/pointnet_kitti

  pointnet_kitti

  Language:Python6233

• jingqiaopoly/LVI-SAM-modified

  Language:C++5301

• wuyiulin/pointnet.pytorch

  pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

  Language:Python400

• Alex-Beh/hdl_localization

  Real-time 3D localization using a (velodyne) 3D LIDAR

  Language:C++1000

• DataspeedInc/ndt_omp

  Multi-threaded and SSE friendly NDT algorithm

  Language:C++1000