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This repository maintains the implementation of "Event-based Stereo Visual Odometry".
Implementation of online photometric calibration (https://vision.in.tum.de/research/vslam/photometric-calibration)
A ROS package tool to analyze the IMU performance.
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
dywuha / evo
Forked from MichaelGrupp/evoPython package for the evaluation of odometry and SLAM
MATLAB code and data for our CRV 2015 paper
MATLAB code and data for our CRV 2015 paper
Monocular Visual-Inertial State Estimator on Mobile Phones
A Robust and Versatile Monocular Visual-Inertial State Estimator
A repository for 3D volumetric (occupancy) maps, providing a generic interface for disparity map and pointcloud insertion, and support for custom sensor error models.
dywuha / sptam
Forked from lrse/sptamS-PTAM: Stereo Parallel Tracking and Mapping
dywuha / libSGM
Forked from fixstars/libSGMStereo Semi Global Matching by cuda
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
This repository contains an implementation of REMODE (REgularized MOnocular Depth Estimation), as described in the paper.
Implementation of Multi-State Constraint Kalman Filter (MSCKF) for Vision-aided Inertial Navigation. This is my master's thesis.
The Kalibr visual-inertial calibration toolbox
dywuha / okvis
Forked from ethz-asl/okvisOKVIS: Open Keyframe-based Visual-Inertial SLAM.
dywuha / libvisensor
Forked from ethz-asl/libvisensorLow level hardware driver for the visual inertial SLAM sensor.
OKVIS: Open Keyframe-based Visual-Inertial SLAM (ROS Version)
Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
dywuha / DeepFace
Forked from RiweiChen/DeepFaceFace analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have been done.
Practise of DeepID for Face Classification