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

Showing 125 of 408 papers

TitleStatusHype
pySLAM: An Open-Source, Modular, and Extensible Framework for SLAMCode7
FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual OdometryCode7
Self-Supervised Geometry-Guided Initialization for Robust Monocular Visual OdometryCode4
Deep Patch Visual SLAMCode4
Reinforcement Learning Meets Visual OdometryCode3
MUSt3R: Multi-view Network for Stereo 3D ReconstructionCode3
LEAP-VO: Long-term Effective Any Point Tracking for Visual OdometryCode3
SiLK -- Simple Learned KeypointsCode2
VOLoc: Visual Place Recognition by Querying Compressed Lidar MapCode2
ESVO2: Direct Visual-Inertial Odometry with Stereo Event CamerasCode2
SR-LIVO: LiDAR-Inertial-Visual Odometry and Mapping with Sweep ReconstructionCode2
VBR: A Vision Benchmark in RomeCode2
PVO: Panoptic Visual OdometryCode2
YOLOPoint Joint Keypoint and Object DetectionCode2
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motionCode2
Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Features and NeRF-realized MappingCode2
Deep Patch Visual OdometryCode2
LIR-LIVO: A Lightweight,Robust LiDAR/Vision/Inertial Odometry with Illumination-Resilient Deep FeaturesCode2
IMU-Aided Event-based Stereo Visual OdometryCode2
IncEventGS: Pose-Free Gaussian Splatting from a Single Event CameraCode2
Multi-Session SLAM with Differentiable Wide-Baseline Pose OptimizationCode2
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic EnvironmentsCode2
Feature-metric Loss for Self-supervised Learning of Depth and EgomotionCode1
FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking DatasetsCode1
Event-based Stereo Visual OdometryCode1
Show:102550
← PrevPage 1 of 17Next →

Benchmark Results

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