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

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Showing 351–375 of 408 papers

TitleStatusHype
Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration—0
DLO: Direct LiDAR Odometry for 2.5D Outdoor Environment—0
Drift Reduction for Monocular Visual Odometry of Intelligent Vehicles using Feedforward Neural Networks—0
Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments—0
DSVO: Direct Stereo Visual Odometry—0
Dynamic Dense RGB-D SLAM using Learning-based Visual Odometry—0
Dynamic Objects Segmentation for Visual Localization in Urban Environments—0
DynaMiTe: A Dynamic Local Motion Model with Temporal Constraints for Robust Real-Time Feature Matching—0
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction—0
DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes—0
Efficient Domain Adaptation for Endoscopic Visual Odometry—0
Efficient Globally-Optimal Correspondence-Less Visual Odometry for Planar Ground Vehicles—0
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation—0
E-Graph: Minimal Solution for Rigid Rotation with Extensibility Graphs—0
EMR-MSF: Self-Supervised Recurrent Monocular Scene Flow Exploiting Ego-Motion Rigidity—0
Enhancing self-supervised monocular depth estimation with traditional visual odometry—0
Epipolar Geometry based Learning of Multi-view Depth and Ego-Motion from Monocular Sequences—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
Evaluation of the visual odometry methods for semi-dense real-time—0
Event-aided Direct Sparse Odometry—0
Event-based Stereo Visual Odometry with Native Temporal Resolution via Continuous-time Gaussian Process Regression—0
Event Camera-based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface—0
Evolution of Visual Odometry Techniques—0
Expansion of Visual Hints for Improved Generalization in Stereo Matching—0
Exploring Deep Spiking Neural Networks for Automated Driving Applications—0
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Benchmark Results

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