Papers Visual Odometry
“Visual Odometry” 태그가 달린 논문 487편 · 필터 해제
Motion-aware Event Suppression for Event Cameras
In this work, we introduce the first framework for Motion-aware Event Suppression, which learns to filter events triggered by IMOs and ego-motion in real time. Our model jointly segments IMOs in the current event stream …
Visual OdometryOpenVO: Open-World Visual Odometry with Temporal Dynamics Awareness
We introduce OpenVO, a novel framework for Open-world Visual Odometry (VO) with temporal awareness under limited input conditions. OpenVO effectively estimates real-world-scale ego-motion from monocular dashcam footage w…
3D ReconstructionVisual OdometryUAV-SEAD: State Estimation Anomaly Dataset for UAVs
Accurate state estimation in Unmanned Aerial Vehicles (UAVs) is crucial for ensuring reliable and safe operation, as anomalies occurring during mission execution may induce discrepancies between expected and observed sys…
Anomaly DetectionVisual OdometryGSO-SLAM: Bidirectionally Coupled Gaussian Splatting and Direct Visual Odometry
We propose GSO-SLAM, a real-time monocular dense SLAM system that leverages Gaussian scene representation. Unlike existing methods that couple tracking and mapping with a unified scene, incurring computational costs, or …
Visual OdometryFeature points evaluation on omnidirectional vision with a photorealistic fisheye sequence -- A report on experiments done in 2014
What is this report: This is a scientific report, contributing with a detailed bibliography, a dataset which we will call now PFSeq for ''Photorealistic Fisheye Sequence'' and make available at https://doi.org/10. 57745/…
Visual OdometryWhen Simultaneous Localization and Mapping Meets Wireless Communications: A Survey
This paper surveys the state-of-the-art in the nexus of SLAM and Wireless Communications, attributing the bidirectional impact of each with a focus on visual SLAM (V-SLAM) integration. We provide an overview of key conce…
Pose EstimationVisual OdometryKeyframe-Based Feed-Forward Visual Odometry
The emergence of visual foundation models has revolutionized visual odometry~(VO) and SLAM, enabling pose estimation and dense reconstruction within a single feed-forward network. However, unlike traditional pipelines th…
Reinforcement LearningPose EstimationVisual Odometry360DVO: Deep Visual Odometry for Monocular 360-Degree Camera
Monocular omnidirectional visual odometry (OVO) systems leverage 360-degree cameras to overcome field-of-view limitations of perspective VO systems. However, existing methods, reliant on handcrafted features or photometr…
Pose EstimationVisual OdometryDefVINS: Visual-Inertial Odometry for Deformable Scenes
Deformable scenes violate the rigidity assumptions underpinning classical visual--inertial odometry (VIO), often leading to over-fitting to local non-rigid motion or to severe camera pose drift when deformation dominates…
Visual OdometryLearning to Anchor Visual Odometry: KAN-Based Pose Regression for Planetary Landing
Accurate and real-time 6-DoF localization is mission-critical for autonomous lunar landing, yet existing approaches remain limited: visual odometry (VO) drifts unboundedly, while map-based absolute localization fails in …
Data AugmentationVisual OdometryTrifocal Tensor and Relative Pose Estimation with Known Vertical Direction
This work presents two novel solvers for estimating the relative poses among views with known vertical directions. The vertical directions of camera views can be easily obtained using inertial measurement units (IMUs) wh…
Autonomous VehiclesPose EstimationVisual OdometrySUPER -- A Framework for Sensitivity-based Uncertainty-aware Performance and Risk Assessment in Visual Inertial Odometry
While many visual odometry (VO), visual-inertial odometry (VIO), and SLAM systems achieve high accuracy, the majority of existing methods miss to assess risks at runtime. This paper presents SUPER (Sensitivity-based Unce…
Visual OdometryMI-SLAM: Magnetic Inertial SLAM Systems
Spatially inhomogeneous magnetic fields offer a valuable, non-visual information source for positioning. Among systems leveraging this, magnetic field-based simultaneous localization and mapping (SLAM) systems are partic…
Visual OdometryOdometry Without Correspondence from Inertially Constrained Ruled Surfaces
Visual odometry techniques typically rely on feature extraction from a sequence of images and subsequent computation of optical flow. This point-to-point correspondence between two consecutive frames can be costly to com…
Visual OdometryEdge DetectionMARVO: Marine-Adaptive Radiance-aware Visual Odometry
Underwater visual localization remains challenging due to wavelength-dependent attenuation, poor texture, and non-Gaussian sensor noise. We introduce MARVO, a physics-aware, learning-integrated odometry framework that fu…
Visual LocalizationVisual OdometryAMB3R: Accurate Feed-forward Metric-scale 3D Reconstruction with Backend
We present AMB3R, a multi-view feed-forward model for dense 3D reconstruction on a metric-scale that addresses diverse 3D vision tasks. The key idea is to leverage a sparse, yet compact, volumetric scene representation a…
3D ReconstructionVisual OdometryMetric, inertially aligned monocular state estimation via kinetodynamic priors
Accurate state estimation for flexible robotic systems poses significant challenges, particularly for platforms with dynamically deforming structures that invalidate rigid-body assumptions. This paper addresses this prob…
Pose EstimationVisual OdometryAutoOdom: Learning Auto-regressive Proprioceptive Odometry for Legged Locomotion
Accurate proprioceptive odometry is fundamental for legged robot navigation in GPS-denied and visually degraded environments where conventional visual odometry systems fail. Current approaches face critical limitations: …
Robot NavigationVisual OdometryDPVO-QAT++: Heterogeneous QAT and CUDA Kernel Fusion for High-Performance Deep Patch Visual Odometry
Deep learning-based Visual SLAM (vSLAM) systems exhibit exceptional geometric reasoning capabilities, yet their prohibitive computational overhead severely restricts deployment on resource-constrained autonomous platform…
Visual OdometrySMF-VO: Direct Ego-Motion Estimation via Sparse Motion Fields
Traditional Visual Odometry (VO) and Visual Inertial Odometry (VIO) methods rely on a 'pose-centric' paradigm, which computes absolute camera poses from the local map thus requires large-scale landmark maintenance and co…
Pose EstimationVisual Odometry