xiaoxueshengyao

GALIP

[CVPR2023] A faster, smaller, and better text-to-image model for large-scale training

stable-diffusion-webui

Stable Diffusion web UI

Text2Poster-ICASSP-22

Official implementation of the ICASSP-2022 paper "Text2Poster: Laying Out Stylized Texts on Retrieved Images"

GPRS_Survey

Benchmark for lidar and visual place recognition

lidar_degeneracy_datasets

LiDAR degeneracy dataset for LiDAR-radar-inertial fusion methods.

accelerated_features

Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!

LightGlue

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

SuperGluePretrainedNetwork

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

SuperPoint

Efficient neural feature detector and descriptor

TEAR-release

SLslam

msckf_vio

Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight

IndoorObstacleDiscovery-RG

[IJCV2023] Official implementation of "Indoor Obstacle Discovery on Reflective Ground via Monocular Camera"

RH-Map

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

LiDAR-Registration-Benchmark

LiDAR-based 3D global registration benchmark.

mad-icp

Minimal, robust, accurate and real-time LiDAR odometry

semantic_suma

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

M2DP

M2DP descriptor of a 3D point cloud

most-lps

Lidar Panoptic Segmentation without Bells and Whistles (IROS 2023)

3d_bbs

dynablox

Real-time detection of diverse dynamic objects in complex environments.

pytorch-tutorials-examples-and-books

PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍

octomap

An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.

dufomap

[RA-L'24] DUFOMap (fork for personal usage)

DynamicMap_Benchmark

The First Dynamic Map Removal Benchmark: open-sourced all the methods and datasets in papers. Continous updating.

active_slam

Implementation of a basic active slam alogorithm in ros and gazebo

Active-SLAM-with-Cartographer

This work contains a modified version of cartographer_frontier_detection and rrt_exploration. We implement an active exploration process and improve its robustness and performance. More details are described in the paper "Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration" (IROS2020).

COIN-LIO

marepo

[CVPR 2024 Highlight] Map-Relative Pose Regression for Visual Re-Localization

far_planner

Fast, Attemptable Route Planner for Navigation in Known and Unknown Environments