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Visual Odometry

44 papers with code · Robots

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ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras

20 Oct 2016raulmur/ORB_SLAM2

We present ORB-SLAM2 a complete SLAM system for monocular, stereo and RGB-D cameras, including map reuse, loop closing and relocalization capabilities.

SIMULTANEOUS LOCALIZATION AND MAPPING VISUAL ODOMETRY

Direct Sparse Odometry

9 Jul 2016JakobEngel/dso

We propose a novel direct sparse visual odometry formulation.

CALIBRATION VISUAL ODOMETRY

Learning Depth from Monocular Videos using Direct Methods

CVPR 2018 yzcjtr/GeoNet

The ability to predict depth from a single image - using recent advances in CNNs - is of increasing interest to the vision community.

DEPTH AND CAMERA MOTION VISUAL ODOMETRY

gvnn: Neural Network Library for Geometric Computer Vision

25 Jul 2016ankurhanda/gvnn

We introduce gvnn, a neural network library in Torch aimed towards bridging the gap between classic geometric computer vision and deep learning.

IMAGE RECONSTRUCTION VISUAL ODOMETRY

PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments

26 May 2017rubengooj/pl-slam

This paper proposes PL-SLAM, a stereo visual SLAM system that combines both points and line segments to work robustly in a wider variety of scenarios, particularly in those where point features are scarce or not well-distributed in the image.

VISUAL ODOMETRY

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

NeurIPS 2019 JiawangBian/SC-SfMLearner-Release

To the best of our knowledge, this is the first work to show that deep networks trained using unlabelled monocular videos can predict globally scale-consistent camera trajectories over a long video sequence.

IMAGE RECONSTRUCTION MULTI-TASK LEARNING VISUAL ODOMETRY

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

NeurIPS 2019 JiawangBian/SC-SfMLearner-Release

To the best of our knowledge, this is the first work to show that deep networks trained using unlabelled monocular videos can predict globally scale-consistent camera trajectories over a long video sequence.

DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

CVPR 2018 Huangying-Zhan/Depth-VO-Feat

Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner.

DEPTH AND CAMERA MOTION MONOCULAR DEPTH ESTIMATION VISUAL ODOMETRY

Geometry-Aware Learning of Maps for Camera Localization

CVPR 2018 NVlabs/geomapnet

Maps are a key component in image-based camera localization and visual SLAM systems: they are used to establish geometric constraints between images, correct drift in relative pose estimation, and relocalize cameras after lost tracking.

3D POSE ESTIMATION CAMERA LOCALIZATION VISUAL ODOMETRY

CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth Prediction

1 Oct 2018yan99033/CNN-SVO

Reliable feature correspondence between frames is a critical step in visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) algorithms.

DEPTH ESTIMATION MOTION ESTIMATION SIMULTANEOUS LOCALIZATION AND MAPPING VISUAL ODOMETRY