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 226–250 of 408 papers

TitleStatusHype
SiLK: Simple Learned Keypoints—0
Simultaneously Learning Corrections and Error Models for Geometry-based Visual Odometry Methods—0
Single-Photon 3D Imaging with Equi-Depth Photon Histograms—0
SLAM in the Dark: Self-Supervised Learning of Pose, Depth and Loop-Closure from Thermal Images—0
Smooth Mesh Estimation from Depth Data using Non-Smooth Convex Optimization—0
Some Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications—0
Sparse2Dense: From direct sparse odometry to dense 3D reconstruction—0
SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion—0
SPOT: Point Cloud Based Stereo Visual Place Recognition for Similar and Opposing Viewpoints—0
Stereo-based Multi-motion Visual Odometry for Mobile Robots—0
Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras—0
Stereo Visual Odometry with Deep Learning-Based Point and Line Feature Matching using an Attention Graph Neural Network—0
Structureless VIO—0
SuperPrimitive: Scene Reconstruction at a Primitive Level—0
Swipe Mosaics from Video—0
Ternary-Type Opacity and Hybrid Odometry for RGB NeRF-SLAM—0
TerrainMesh: Metric-Semantic Terrain Reconstruction from Aerial Images Using Joint 2D-3D Learning—0
The Aqualoc Dataset: Towards Real-Time Underwater Localization from a Visual-Inertial-Pressure Acquisition System—0
The Empirical Impact of Forgetting and Transfer in Continual Visual Odometry—0
Theory and Practice of Structure-From-Motion Using Affine Correspondences—0
The POLAR Traverse Dataset: A Dataset of Stereo Camera Images Simulating Traverses across Lunar Polar Terrain under Extreme Lighting Conditions—0
The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigation—0
Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry—0
Tightly-Coupled LiDAR-Visual SLAM Based on Geometric Features for Mobile Agents—0
Topometric Localization with Deep Learning—0
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Benchmark Results

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