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https://github.com/seungchan-mok/awesome_autonomous_vehicle_contents

자율주행 엔지니어를 위한 컨텐츠 모음
https://github.com/seungchan-mok/awesome_autonomous_vehicle_contents

List: awesome_autonomous_vehicle_contents

autonomous-contents autonomous-vehicles awesome-list

Last synced: 16 days ago
JSON representation

자율주행 엔지니어를 위한 컨텐츠 모음

Host: GitHub
URL: https://github.com/seungchan-mok/awesome_autonomous_vehicle_contents
Owner: seungchan-mok
Created: 2020-02-24T05:01:03.000Z (almost 5 years ago)
Default Branch: master
Last Pushed: 2021-04-09T08:14:50.000Z (over 3 years ago)
Last Synced: 2024-05-20T05:36:12.584Z (7 months ago)
Topics: autonomous-contents, autonomous-vehicles, awesome-list
Homepage: https://msc9533.github.io/awesome_autonomous_vehicle_contents/
Size: 57.6 KB
Stars: 25
Watchers: 2
Forks: 5
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

ultimate-awesome - awesome_autonomous_vehicle_contents - 자율주행 엔지니어를 위한 컨텐츠 모음. (Other Lists / Monkey C Lists)

README

        # Autonomous_contents

자율주행 엔지니어를 위한 컨텐츠 모음 (SLAM, Deep Learning, Computer Vision..)

## Awesome projects

- [key points estimation and point instance segmentation approach for lane detection](https://github.com/koyeongmin/PINet)

- [Learning Lightweight Lane Detection CNNs by Self Attention Distillation](https://github.com/cardwing/Codes-for-Lane-Detection)

- [ORB-SLAM2](https://github.com/raulmur/ORB_SLAM2)

- [google Cartographer](https://google-cartographer.readthedocs.io/en/latest/)

- [hdl_graph_slam](https://github.com/koide3/hdl_graph_slam)

## Lecture & Tutorials & Text Book

- [Freiburg - Introduction to Mobile Robotics - SS 2018](http://ais.informatik.uni-freiburg.de/teaching/ss18/robotics/)

- [Stanford CS231n: Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu/)

- [숭실대학교 김강희 교수님 Autoware workshop 2019](https://github.com/khkim545/autoware_workshop_2019)

- [Google-Cartographer documentation](https://google-cartographer.readthedocs.io/en/latest/)

- [YOLO v3 윈도우 버전 설치 및 튜토리얼 한방에 정리](https://studyingcoder.blogspot.com/2019/04/open-source-yolo-v3.html)

- [PythonRobotics documentation](https://pythonrobotics.readthedocs.io/en/latest/)

- [How to implement a YOLO (v3) object detector from scratch in PyTorch](https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/)

- [Developing an autonomous driving ML algorithm using OS1 intensity data](https://ouster.com/blog/developing-an-autonomous-driving-ml-algorithm-using-os1-intensity-data/)

- [Probabilistic Robotic pdf](https://docs.ufpr.br/~danielsantos/ProbabilisticRobotics.pdf)

- [Mathematics for Machine Learning - textbook](https://mml-book.github.io/)

- [An Invitation to 3D Vision: A Tutorial for Everyone](https://github.com/sunglok/3dv_tutorial)

- [opensfm docs](https://www.opensfm.org/docs/)

- [1시간만에 GAN(Generative Adversarial Network) 완전 정복하기](https://www.youtube.com/watch?v=odpjk7_tGY0&feature=youtu.be)

- [event-based_vision_resources](https://github.com/uzh-rpg/event-based_vision_resources)

- [NIPS 2016 Tutorial: Generative Adversarial Networks](https://arxiv.org/abs/1701.00160)

- [Python - GraphSLAM](https://github.com/JeffLIrion/python-graphslam)

## 읽어보면 좋을만한 포스팅 or Links

- [팔로우 하기 좋은 SLAM 연구자 링크](https://cv-learn.com/SLAM-75cbbf7e653e470caf31629385eae997)

- [Least Squares (최소자승법)](http://jinyongjeong.github.io/2017/02/26/lec12_Least_square/)

- [최소자승법 이해와 다양한 활용예 (Least Square Method)](https://darkpgmr.tistory.com/56)

- [모든 컴퓨터 비젼 연구자들이 알아야 할 20개의 techniques](https://200315193.tistory.com/2028)

- [영상 특징점(keypoint)추출방법](https://darkpgmr.tistory.com/131?category=460965)

- [CV 개발 라이브러리](https://www.notion.so/CV-42cdaa2d211547eeba40f958ed9ae1cb)

- [카메라 캘리브레이션 (Camera Calibration)](https://darkpgmr.tistory.com/32)

- [영상의 기하학적 해석 - 영상의 지면 투영(ground projection)](https://darkpgmr.tistory.com/153?category=460965)

- [RANSAC의 이해와 영상처리 활용](https://darkpgmr.tistory.com/61)

- [영상분할 - Otsu Thresholding(이진화)](https://j07051.tistory.com/364)

- [다익스트라 알고리즘(Dijkstra Algorithm)](https://hsp1116.tistory.com/42)

- [Kalman filter와 Extended Kalman filter에 대한 설명](http://jinyongjeong.github.io/2017/02/14/lec03_kalman_filter_and_EKF/)

- [Structure from Motion Tutorial](https://imkaywu.github.io/tutorials/sfm/)

- [Graph SLAM: A Noob’s Guide to Simultaneous Localization And Mapping](https://medium.com/@krunalkshirsagar/graph-slam-a-noobs-guide-to-simultaneous-localization-and-mapping-aaff4ee91dee)

- [Awesome Interaction-aware Behavior and Trajectory Prediction](https://github.com/jiachenli94/Awesome-Interaction-aware-Trajectory-Prediction)

- [PTAM(Parallel Tracking and Mapping)과 PTAMM](https://darkpgmr.tistory.com/129)

- [딥러닝 기반 3차원 비전 객체 인식 PointNet 분석](http://daddynkidsmakers.blogspot.com/2017/07/3-pointnet.html)

## Language & Frameworks

- [C언어 코딩 도장](https://dojang.io/course/view.php?id=2)

- [파이썬 코딩 도장](https://dojang.io/course/view.php?id=7)

- [ROS Tutorials](http://wiki.ros.org/ROS/Tutorials)

- [ROS 강의 by 표윤석](https://www.youtube.com/playlist?list=PLRG6WP3c31_VIFtFAxSke2NG_DumVZPgw)

## 커뮤니티

- [TensorFlow KR](https://www.facebook.com/groups/TensorFlowKR/)

- [SLAM KR](https://www.facebook.com/groups/slamkr)

- [V.AIS](https://open.kakao.com/o/ghU9D1o)

- [자율주행을 좋아하는 사람들](https://open.kakao.com/o/geMJ6H2)

- [저희는_SLAM_마스터가_될겁니다](https://open.kakao.com/o/g8T5kxLb)

## 기타자료

- [논문검색프로그램 - Publish or Perish](https://harzing.com/resources/publish-or-perish)

- [SLAM DUNK Season 2 Play list](https://www.youtube.com/playlist?list=PLubUquiqNQdP_H6uUmU-9f0y_LheA3Hil)

- [그래픽드라이버 버전별 cuda 호환성](https://github.com/NVIDIA/nvidia-docker/wiki/CUDA)

- [awesome-lane-detection](https://github.com/amusi/awesome-lane-detection)

- [수식 캡쳐 - tex 변환](https://mathpix.com/)

- [Lidar Point clound processing for Autonomous Driving](https://github.com/beedotkiran/Lidar_For_AD_references)

- [V.AIS 자료모음](https://v-ais.github.io/blog/study/)

- [NAVER Deview 2019](https://deview.kr/2019/schedule)

- [머신러닝 / 딥러닝 도서비교표](https://docs.google.com/spreadsheets/d/1zpLFAPZ8NA6V09JUUU66g_lvpVra24B_ZTDHunM2O8c/edit?fbclid=IwAR26m1D3T4CatHHtY5Ff8fF3gZ8RRCmAuVS3g5V3_i-rdx73okSCWT0bOOs#gid=2144436952)

- [Free and low cost resources for graduate students, postdocs, and early career researchers](https://docs.google.com/document/d/1IFbHIN5OOAO0qz-VfCU9nEx4-x6CfArj1-d8ylA2vsU/mobilebasic)

- [자율주행 기업 리스트](https://selfdriving.fyi/)

- [Awesome SLAM KR List](https://github.com/slam-research-group-kr/awesome_SLAM_KR_List)

- [Awesome SLAM Dataset List](https://sites.google.com/view/awesome-slam-datasets/home)

## Dataset & Simulator

- [NAVER LABS HD MAP DATASET](https://hdmap.naverlabs.com/)

- [국토지리정보원 HD MAP](http://map.ngii.go.kr/ms/pblictn/preciseRoadMap.do)

- [KAIST URBAN DATA SET](https://irap.kaist.ac.kr/dataset/)

- [KAIST Multispectral Pedestrian Detection Benchmark](https://sites.google.com/site/pedestrianbenchmark/)

- [KITTI DATASET](http://www.cvlibs.net/datasets/kitti/)

- [Partitioned Nordland Dataset](http://webdiis.unizar.es/~jmfacil/pr-nordland/)

- [ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes](http://www.scan-net.org/)

- [gazebo](http://gazebosim.org/)

- [AirSim](https://github.com/microsoft/AirSim)

- [Carla](https://github.com/carla-simulator/carla)

- [Apollo](http://apollo.auto/platform/simulation.html)

- [LGSVL](https://www.lgsvlsimulator.com/)

## Contribution

`미분류 Contents`에 자율 주행 개발 관련 링크를 공유해주세요!

## 미분류 Contents

### 이곳에 있는 링크는 분류를 거쳐 카테고리로 이동됩니다.