Beast code in Giters

GXU-doudou's starred repositories

OpenDevin

🐚 OpenDevin: Code Less, Make More

Language:PythonMIT28694 279 1167

ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Language:PythonAGPL-3.026222 155 7885

SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

Language:PythonMIT11970 90 326

awesome-lane-detection

A paper list of lane detection.

2877 140 13

FAST_LIO

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

Language:C++GPL-2.02428 51 306

lanenet-lane-detection

Unofficial implemention of lanenet model for real time lane detection

Language:PythonApache-2.02309 54 559

SensorsCalibration

OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

Language:C++Apache-2.02221 48 154

bevfusion

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

Language:PythonApache-2.02153 42 606

Ultra-Fast-Lane-Detection

Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

Language:PythonMIT1769 27 362

robot_localization

robot_localization is a package of nonlinear state estimation nodes. The package was developed by Charles River Analytics, Inc. Please ask questions on answers.ros.org.

Language:C++NOASSERTION1308 55 432

faster-lio

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels

Language:C++GPL-2.01000 26 65

MapTR

[ICLR'23 Spotlight] MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Language:PythonMIT989 40 170

LIO-Livox

A Robust LiDAR-Inertial Odometry for Livox LiDAR

Language:C++BSD-3-Clause627 15 74

LaneATT

Code for the paper entitled "Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection" (CVPR 2021)

Language:PythonMIT614 14 135

AVP-SLAM-PLUS

An implementation of AVP-SLAM and some new contributions

Language:C++AGPL-3.0597 14 17

LIO_SAM_6AXIS

LIO_SAM for 6-axis IMU and GNSS.

Language:C++563 12 80

LiDAR-MOS

(LMNet) Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data (RAL/IROS 2021)

Language:PythonMIT562 14 74

FAST_LIO_LOCALIZATION

A simple localization framework that can re-localize in built maps based on FAST-LIO.

Language:C++GPL-2.0547 9 37

cuPCL

A project demonstrating how to use the libs of cuPCL.

Language:C++MIT538 20 57

removert

Remove then revert (IROS 2020)

Language:C++516 18 31

STD

A 3D point cloud descriptor for place recognition

Language:C++GPL-2.0514 27 35

Awesome_Dynamic_SLAM

Dynamic SLAM, Life-long SLAM Research(Lidar, Visual, Sensor Fusion etc.)

MIT505 22 1

ros1_bridge

ROS 2 package that provides bidirectional communication between ROS 1 and ROS 2

Language:C++Apache-2.0424 31 188

SuperFusion

[ICRA 2024] SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation

Language:PythonGPL-3.0292 25 12

4DMOS

Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions (RAL 2022)

Language:PythonMIT259 8 32

DBScan-PCL-Optimized

DBScan algorithm using Octrees to cluster 3D points in a space with PCL Library

Language:C++175 7 5

This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.

Language:Jupyter Notebook106 5 1

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