Papers Visual Odometry
“Visual Odometry” 태그가 달린 논문 487편 · 필터 해제
Trinity: Unifying Class-Agnostic Terrain and Semantic Segmentation for Unstructured Outdoor Environments by Leveraging Synthetic Data
Terrain understanding is fundamental for mobile robots operating in unstructured outdoor environments. Existing vision-based traversability estimation methods rely on robot-specific annotations or semantic class mappings…
Semantic SegmentationVisual OdometryFusionCore: A 23-State Unscented Kalman Filter for IMU, Wheel Encoder, GPS, and Visual SLAM Fusion in ROS 2
We present FusionCore, an open-source ROS 2 sensor fusion package that fuses IMU, wheel encoder odometry, GPS, and Visual SLAM pose into a single 100 Hz odometry stream using a 23-state Unscented Kalman Filter (UKF). The…
Visual OdometryLC-Flow: Learning Local Continuous Optical Flow and Confidence from events
Event cameras capture brightness changes asynchronously with microsecond resolution, yet existing optical flow methods fail to fully exploit this temporal continuity. Frame-based approaches impose artificial accumulation…
Visual OdometryExtending Deep Event Visual Odometry with Sparse Point-Cloud Export
Event cameras are well suited for visual odometry under high-speed motion and challenging lighting conditions due to their low latency, high temporal resolution, and high dynamic range. Deep Event Visual Odometry (DEVO) …
Visual OdometryEpiDiffVO: Geometry-Aware Epipolar Diffusion for Robust Visual Odometry
Estimating relative pose from image pairs fundamentally requires only a minimal subset of geometrically consistent correspondences. However, most learning-based approaches rely on dense matching or direct regression, lea…
Graph Neural NetworkPose EstimationVisual OdometryAERO-VIS: Asynchronous Event-based Real-time Onboard Visual-Inertial SLAM
The robustness of event cameras to high dynamic range and motion blur holds the potential to improve visual odometry systems in challenging environments. Although their high temporal resolution does not require synchrono…
Visual OdometryEvent-based SLAM Benchmark for High-Speed Maneuvers
Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in high-speed maneuver…
Visual OdometryPose TrackingPoseFM: Relative Camera Pose Estimation Through Flow Matching
Monocular visual odometry (VO) is a fundamental computer vision problem with applications in autonomous navigation, augmented reality and more. While deep learning-based methods have recently shown superior accuracy comp…
Camera Pose EstimationVisual OdometryRailway Artificial Intelligence Learning Benchmark (RAIL-BENCH): A Benchmark Suite for Perception in the Railway Domain
Automated train operation on existing railway infrastructure requires robust camera-based perception, yet the railway domain lacks public benchmark suites with standardized evaluation protocols that would enable reproduc…
Multi-Object TrackingObject DetectionVisual OdometryLine DetectionRadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment
Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most radar SLAM pipelines still rely heavily on frame-to-frame odometry, whi…
Visual OdometryVGGT-SLAM++
We introduce VGGT-SLAM++, a complete visual SLAM system that leverages the geometry-rich outputs of the Visual Geometry Grounded Transformer (VGGT). The system comprises a visual odometry (front-end) fusing the VGGT feed…
Visual Place RecognitionVisual OdometryDINO-VO: Learning Where to Focus for Enhanced State Estimation
We present DINO Patch Visual Odometry (DINO-VO), an end-to-end monocular visual odometry system with strong scene generalization. Current Visual Odometry (VO) systems often rely on heuristic feature extraction strategies…
Visual OdometryViBA: Implicit Bundle Adjustment with Geometric and Temporal Consistency for Robust Visual Matching
Most existing image keypoint detection and description methods rely on datasets with accurate pose and depth annotations, limiting scalability and generalization, and often degrading navigation and localization performan…
Keypoint DetectionVisual OdometryHyVGGT-VO: Tightly Coupled Hybrid Dense Visual Odometry with Feed-Forward Models
Dense visual odometry (VO), which provides pose estimation and dense 3D reconstruction, serves as the cornerstone for applications ranging from robotics to augmented reality. Recently, feed-forward models have demonstrat…
Computational Efficiency3D ReconstructionPose EstimationVisual OdometryImage-Conditioned Adaptive Parameter Tuning for Visual Odometry Frontends
Resource-constrained autonomous robots rely on sparse direct and semi-direct visual-(inertial)-odometry (VO) pipelines, as they provide a favorable tradeoff between accuracy, robustness, and computational cost. However, …
Reinforcement LearningVisual OdometryBenchmarking Visual Feature Representations for LiDAR-Inertial-Visual Odometry Under Challenging Conditions
Accurate localization in autonomous driving is critical for successful missions including environmental mapping and survivor searches. In visually challenging environments, including low-light conditions, overexposure, i…
Autonomous DrivingVisual OdometryFull Stack Navigation, Mapping, and Planning for the Lunar Autonomy Challenge
We present a modular, full-stack autonomy system for lunar surface navigation and mapping developed for the Lunar Autonomy Challenge. Operating in a GNSS-denied, visually challenging environment, our pipeline integrates …
Semantic SegmentationMotion PlanningVisual OdometryIndustrial cuVSLAM Benchmark & Integration
This work presents a comprehensive benchmark evaluation of visual odometry (VO) and visual SLAM (VSLAM) systems for mobile robot navigation in real-world logistical environments. We compare multiple visual odometry appro…
Robot NavigationVisual OdometryEdged USLAM: Edge-Aware Event-Based SLAM with Learning-Based Depth Priors
Conventional visual simultaneous localization and mapping (SLAM) algorithms often fail under rapid motion, low illumination, or abrupt lighting transitions due to motion blur and limited dynamic range. Event cameras miti…
Visual OdometryFLIGHT: Fibonacci Lattice-based Inference for Geometric Heading in real-Time
Estimating camera motion from monocular video is a fundamental problem in computer vision, central to tasks such as SLAM, visual odometry, and structure-from-motion. Existing methods that recover the camera's heading und…
Visual Odometry