gogojjh

gogojjh's repositories

M-LOAM

Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration

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ESVO_extension

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lidar_appearance_calibration

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glimpse_nvblox_ros1

Static fork from Nvidia's Nvblox repo. Converted to ROS-1 and adapted for 3d-LiDAR generated depth images

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gogojjh.github.io

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multi_sensor_calibration

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awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

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ICP

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LCECalib

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lio-mapping

Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)

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nvblox

A GPU-accelerated TSDF and ESDF library for robots equipped with RGB-D cameras.

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996.ICU

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

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cinder

A clean, responsive MkDocs theme

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dsl

Implementation of Monocular Direct Sparse Localization in a Prior 3D Surfel Map (DSL)

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ESVO

This repository maintains the implementation of "Event-based Stereo Visual Odometry".

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glog

C++ implementation of the Google logging module

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karpathy.github.io

my blog

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kdTree

An implementation of kdTree in 2D space

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Kimera

Index repo for Kimera code

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Kimera-VIO

Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation.

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kiss-icp

KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done in the Right Way https://arxiv.org/pdf/2209.15397.pdf

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markdown-it

Markdown parser, done right. 100% CommonMark support, extensions, syntax plugins & high speed

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plycal

Extrinsic calibration of the camera and LiDAR via polygon plane

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ppe

Probabilistic plane extraction

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probreg

Point cloud registration using probabilistic model (CPD/GMMReg/SVR/GMMTree/FilterReg)

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rpg_emvs

Code for the paper "EMVS: Event-based Multi-View Stereo" (IJCV, 2018)

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snap

SNAP: Self-supervised Neural Maps for Visual Positioning and Semantic Understanding (NeurIPS 2023)

Apache-2.0000

VINS-Fusion

An optimization-based multi-sensor state estimator

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VINS-Mono

A Robust and Versatile Monocular Visual-Inertial State Estimator

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VIRL

Code for V-IRL: Grounding Virtual Intelligence in Real Life

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