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🚀 Deep learning includes superpoint-superglue(C++, TensorRT), and traditional algorithms include zkaze, surf, ORB, etc.
[CVPR'24] SNI-SLAM: Semantic Neural Implicit SLAM
Visual-inertial-wheel fusion odometry, better performance in scenes with drastic changes in light
Roadmap to become a Visual-SLAM developer in 2023
A visual-inertial SLAM framework integrated deep learning features
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
Semantic ELevation (SEL) map is a semantic Bayesian inferencing framework for real-time elevation mapping and terrain property estimation from RGB-D images.
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Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.
Real-time Radar SLAM: ORORA + ScanContext
Gaussian Process-based Traversability Analysis for Terrain Mapless Navigation
lidar-slam,gtsam,vgicp,cuda,loop_finding,mapping.
Dynamic SLAM, Life-long SLAM Research(Lidar, Visual, Sensor Fusion etc.)
Fast Incremental Euclidean Distance Fields for Online Motion Planning of Aerial Robots
Robot-centric elevation mapping for rough terrain navigation
Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians
[SIGGRAPH'24] 2D Gaussian Splatting for Geometrically Accurate Radiance Fields
3D Gaussian Splatting, reimagined: Unleashing unmatched speed with C++ and CUDA from the ground up!
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"