JoannaZhj's Stars
justfont/AllPunType
諧靈附體 AllPunType:一套將所有生肖的相近音漢字,全部替換成生肖本字的字型家族。在年節將至、需要吉祥話發想時,歡迎使用本字型進行靈感激盪,或煩死朋友。
CSAILVision/semantic-segmentation-pytorch
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
ros2/examples
Example packages for ROS 2
ros2/demos
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
xmu-xiaoma666/FightingCV-Paper-Reading
⭐⭐⭐FightingCV Paper Reading, which helps you understand the most advanced research work in an easier way 🍀 🍀 🍀
microsoft/admin-torch
Understanding the Difficulty of Training Transformers
yanyan-li/SLAM-BOOK
这是一本关于SLAM的书稿,希望能清楚的介绍SLAM系统中的使用的几何方法和深度学习方法。书稿最后应该会达到200页左右,书稿每章对应的代码也会被整理出来。
IntelRealSense/librealsense
Intel® RealSense™ SDK
youngguncho/awesome-slam-datasets
A curated list of awesome datasets for SLAM
YiChenCityU/Recent_SLAM_Research
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整,暫停更新
fistyee/MixPro
🔥MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer [Official, ICLR 2023]
aofrancani/TSformer-VO
Implementation of the paper "Transformer-based model for monocular visual odometry: a video understanding approach".
zihangJiang/TokenLabeling
Pytorch implementation of "All Tokens Matter: Token Labeling for Training Better Vision Transformers"
Vincentqyw/Recent-Stars-2024
🔥SLAM, VIsual localization, keypoint detection, Image matching, Pose/Object tracking, Depth/Disparity/Flow Estimation, 3D-graphic, etc. related papers and code
SilenceOverflow/Awesome-SLAM
A curated list of SLAM resources
amusi/Deep-Learning-Interview-Book
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
virginiakm1988/ML2022-Spring
**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring
MichaelBeechan/VO-SLAM-Review
SLAM is mainly divided into two parts: the front end and the back end. The front end is the visual odometer (VO), which roughly estimates the motion of the camera based on the information of adjacent images and provides a good initial value for the back end.The implementation methods of VO can be divided into two categories according to whether features are extracted or not: feature point-based methods, and direct methods without feature points. VO based on feature points is stable and insensitive to illumination and dynamic objects
qxiaofan/awesome_3d_slam_resources
记录3D视觉、VSLAM、计算机视觉的干货资料。
VisionerTech/ORB_SLAM2_Unity
ORB_SLAM2 Unity example
nebula-beta/SLAM-Jobs
这个一份SLAM/SFM求职指南,旨在帮助视觉SLAM/SFM的小伙伴们能够找到更好的工作。
changh95/visual-slam-roadmap
Roadmap to become a Visual-SLAM developer in 2023
electech6/LearnSLAM
SLAM研习社
kanster/awesome-slam
A curated list of awesome SLAM tutorials, projects and communities.