SOTAVerified

Visual Odometry

Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.

Source: Bi-objective Optimization for Robust RGB-D Visual Odometry

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 408 papers

TitleStatusHype
ObVi-SLAM: Long-Term Object-Visual SLAM—0
Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras—0
OmniSLAM: Omnidirectional Localization and Dense Mapping for Wide-baseline Multi-camera Systems—0
On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation—0
Online Learning of Wheel Odometry Correction for Mobile Robots with Attention-based Neural Network—0
Online Photometric Calibration for Auto Exposure Video for Realtime Visual Odometry and SLAM—0
ORB-SfMLearner: ORB-Guided Self-supervised Visual Odometry with Selective Online Adaptation—0
OSPC: Online Sequential Photometric Calibration—0
PCA Event-Based Optical Flow for Visual Odometry—0
PIVO: Probabilistic Inertial-Visual Odometry for Occlusion-Robust Navigation—0
Pixel-Wise Prediction based Visual Odometry via Uncertainty Estimation—0
Playing for Benchmarks—0
PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning—0
Pose Graph Optimization for Unsupervised Monocular Visual Odometry—0
Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learning—0
Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry—0
Probabilistic Regression of Rotations using Quaternion Averaging and a Deep Multi-Headed Network—0
Pseudo-LiDAR for Visual Odometry—0
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry—0
Realtime Edge-Based Visual Odometry for a Monocular Camera—0
Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments—0
Recurrent Neural Network for (Un-)Supervised Learning of Monocular Video Visual Odometry and Depth—0
Resilient Simultaneous Localization and Mapping Fusing Ultra Wide Band Range Measurements and Visual Odometry—0
Robot Localization and Mapping Final Report -- Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry—0
Robust Dense Mapping for Large-Scale Dynamic Environments—0
Robust Edge-Direct Visual Odometry based on CNN edge detection and Shi-Tomasi corner optimization—0
Robust Monocular Visual Odometry using Curriculum Learning—0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model—0
Robust RGB-D Odometry Using Point and Line Features—0
Robust Monocular Edge Visual Odometry through Coarse-to-Fine Data Association—0
Robust Stereo Feature Descriptor for Visual Odometry—0
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
RoMeO: Robust Metric Visual Odometry—0
SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment—0
Salient Sparse Visual Odometry With Pose-Only Supervision—0
Scale-Awareness of Light Field Camera based Visual Odometry—0
Scale Recovery for Monocular Visual Odometry Using Depth Estimated With Deep Convolutional Neural Fields—0
Scene-agnostic Pose Regression for Visual Localization—0
Scene Motion Decomposition for Learnable Visual Odometry—0
Secure Navigation using Landmark-based Localization in a GPS-denied Environment—0
Self-Improving Visual Odometry—0
Self-Supervised Deep Visual Odometry with Online Adaptation—0
Self-supervised Pretraining and Finetuning for Monocular Depth and Visual Odometry—0
Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry—0
Semantic Nearest Neighbor Fields Monocular Edge Visual-Odometry—0
Semi-Dense Visual Odometry for RGB-D Cameras Using Approximate Nearest Neighbour Fields—0
Semi-Supervised Pipe Video Temporal Defect Interval Localization—0
Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry—0
SfMLearner++: Learning Monocular Depth & Ego-Motion using Meaningful Geometric Constraints—0
SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation with Stacked Generative Adversarial Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CIVORelative Position Error Translation [cm]1.36—Unverified