John Liang's repositories
AiLearning
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
ARCore-Data-Logger
Android app to save ARCore results (Visual-Inertial Odometry) to a series of text files for offline use.
awesome-hand-pose-estimation
Awesome work on hand pose estimation/tracking
awesome-slam-datasets
SLAM数据集---A curated list of awesome datasets for SLAM
BERT-for-Unity
Bidirectional Encoder Representations from Transformers technique for Unity game engine
Books_Robot_SLAM_Navigation
This project is supporting code for the book of Robot SLAM Navigation Core Technology and the Actual Combat.
CollaborativeSLAMDataset
The dataset associated with our ISMAR 2018 paper on Collaborative SLAM.
CompetitiveProgrammingQuestionBank
This repository contains all the popular competitive programming and DSA questions with solutions.
DeepMatchVO
Implementation of ICRA 2019 paper: Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation
DeepVO-1
Deep Monocular Visual Odometry using PyTorch (Experimental)
demon
DeMoN: Depth and Motion Network
dense-orbslam2
check
DUI_VIO
Depth uncertainty incorporated VIO
hand-graph-cnn
3D Hand Shape and Pose Estimation from a Single RGB Image
HandPoseBarracuda
Hand and finger tracking solution (MediaPipe Hands) for Unity Barracuda
mediapipe-models
mediapipe-models
MeshTransformer
Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"
mobilehand
MobileHand: Real-time 3D Hand Shape and Pose Estimation from Color Image
ORB_SLAM2_zhushiban
Check
pnec
[CVPR 2022] README.md The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions
PocketSphinxUnityDemo
A sample Unity project showing how to use PocketSphinx.
pytorch-deepvo
An Implementation of DeepVO with CNN / CNN-LSTM
ros_21_tutorials
《古月 · ROS入门21讲》课件&源码
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
transformer-tensorflow
Implementation of Transformer Model in Tensorflow
VINS-Mono
A Robust and Versatile Monocular Visual-Inertial State Estimator
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