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a-loam

Advanced implementation of LOAM

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

bevfusion

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

bevplace

A rotation-invariant, generalizable, and SOTA LiDAR place recognition method.

ct_icp

CT-ICP: Continuous-Time LiDAR Odometry

disk

Disk code release

dockerlabs

Docker - Beginners | Intermediate | Advanced

event-based_vision_resources

gnnpapers

Must-read papers on graph neural networks (GNN)

hierarchical-localization

Visual localization made easy with hloc

image-matching-webui

🤗 image matching toolbox webui

introduction-to-autonomous-robots

Introduction to Autonomous Robots

kiss-icp

A LiDAR odometry pipeline that just works

lego-loam

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

lightglue

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

lio-sam

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

loam_noted

loam code noted in Chinese（loam中文注解版）

mapclosures

Effectively Detecting Loop Closures using Point Cloud Density Maps

orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

pin_slam

📍PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency

pointnetvlad

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018

pykitti

Python tools for working with KITTI data.

pylidar-slam

slam-1

learning SLAM,curse,paper and others

slam_in_autonomous_driving

《自动驾驶中的SLAM技术》对应开源代码

soe-net

The codes for CVPR2021 Oral paper 'SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition'

superpoint

Efficient neural feature detector and descriptor

superpointpretrainednetwork

PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking (https://arxiv.org/abs/1712.07629)

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