Papers Simultaneous Localization and Mapping
“Simultaneous Localization and Mapping” 태그가 달린 논문 572편 · 필터 해제
Inertial Guided Uncertainty Estimation of Feature Correspondence in Visual-Inertial Odometry/SLAM
Visual odometry and Simultaneous Localization And Mapping (SLAM) has been studied as one of the most important tasks in the areas of computer vision and robotics, to contribute to autonomous navigation and augmented real…
Autonomous NavigationSimultaneous Localization and MappingVisual OdometryResilient Simultaneous Localization and Mapping Fusing Ultra Wide Band Range Measurements and Visual Odometry
In this paper we consider a Simultaneous Localization and Mapping (SLAM) problem for a moving agent using Visual Odometry (VO) while measuring the range from a set of Ultra Wide Band (UWB) antennas, deployed in unknown p…
PositionSimultaneous Localization and MappingVisual OdometryTivNe-SLAM: Dynamic Mapping and Tracking via Time-Varying Neural Radiance Fields
Previous attempts to integrate Neural Radiance Fields (NeRF) into the Simultaneous Localization and Mapping (SLAM) framework either rely on the assumption of static scenes or require the ground truth camera poses, which …
NeRFSimultaneous Localization and MappingTowards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos using NeRFs
Given that a conventional laparoscope only provides a two-dimensional (2-D) view, the detection and diagnosis of medical ailments can be challenging. To overcome the visual constraints associated with laparoscopy, the us…
Depth EstimationSimultaneous Localization and MappingLearning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors
Learning neural implicit representations has achieved remarkable performance in 3D reconstruction from multi-view images. Current methods use volume rendering to render implicit representations into either RGB or depth i…
3D ReconstructionSimultaneous Localization and MappingJointly Optimized Global-Local Visual Localization of UAVs
Navigation and localization of UAVs present a challenge when global navigation satellite systems (GNSS) are disrupted and unreliable. Traditional techniques, such as simultaneous localization and mapping (SLAM) and visua…
RetrievalSimultaneous Localization and MappingVisual LocalizationVisual Odometry3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments
The existence of variable factors within the environment can cause a decline in camera localization accuracy, as it violates the fundamental assumption of a static environment in Simultaneous Localization and Mapping (SL…
3D Object DetectionCamera Localizationobject-detectionObject Detection+2HI-SLAM: Monocular Real-time Dense Mapping with Hybrid Implicit Fields
In this letter, we present a neural field-based real-time monocular mapping framework for accurate and dense Simultaneous Localization and Mapping (SLAM). Recent neural mapping frameworks show promising results, but rely…
global-optimizationSimultaneous Localization and MappingMonocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelines
With the rise of deep learning, there is a fundamental change in visual simultaneous localization and mapping (SLAM) algorithms toward developing different modules trained as end-to-end pipelines. However, regardless of …
Monocular Visual OdometrySimultaneous Localization and MappingLanguage-EXtended Indoor SLAM (LEXIS): A Versatile System for Real-time Visual Scene Understanding
Versatile and adaptive semantic understanding would enable autonomous systems to comprehend and interact with their surroundings. Existing fixed-class models limit the adaptability of indoor mobile and assistive autonomo…
Scene UnderstandingSimultaneous Localization and MappingDVI-SLAM: A Dual Visual Inertial SLAM Network
Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress. However, how to make full use of visual information as well as better integrate with inertial measure…
Simultaneous Localization and MappingDynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines encounter difficulties in accurately tra…
Camera LocalizationCamera Pose EstimationDynamic ReconstructionNeRF+4Poster: Making Edge-assisted LiDAR Perceptions Robust to Lossy Point Cloud Compression
Real-time light detection and ranging (LiDAR) perceptions, e.g., 3D object detection and simultaneous localization and mapping are computationally intensive to mobile devices of limited resources and often offloaded on t…
3D Object Detectionobject-detectionObject DetectionSimultaneous Localization and MappingGO-SLAM: Global Optimization for Consistent 3D Instant Reconstruction
Neural implicit representations have recently demonstrated compelling results on dense Simultaneous Localization And Mapping (SLAM) but suffer from the accumulation of errors in camera tracking and distortion in the reco…
3D Reconstructionglobal-optimizationPose EstimationSimultaneous Localization and MappingNTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping
Simultaneous Localization and Mapping (SLAM) is moving towards a robust perception age. However, LiDAR- and visual- SLAM may easily fail in adverse conditions (rain, snow, smoke and fog, etc.). In comparison, SLAM based …
object-detectionObject DetectionSimultaneous Localization and MappingDeep Learning for Visual Localization and Mapping: A Survey
Deep learning based localization and mapping approaches have recently emerged as a new research direction and receive significant attentions from both industry and academia. Instead of creating hand-designed algorithms b…
Deep LearningSimultaneous Localization and MappingSurveyVisual Localization+1VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition
LiDAR-based place recognition plays a crucial role in Simultaneous Localization and Mapping (SLAM) and LiDAR localization. Despite the emergence of various deep learning-based and hand-crafting-based methods, rotation-in…
Computational EfficiencySimultaneous Localization and MappingSLAM for Multiple Extended Targets using 5G Signal
5th Generation (5G) mobile communication systems operating at around 28 GHz have the potential to be applied to simultaneous localization and mapping (SLAM). Most existing 5G SLAM studies estimate environment as many poi…
Simultaneous Localization and MappingStereo Visual Odometry with Deep Learning-Based Point and Line Feature Matching using an Attention Graph Neural Network
Robust feature matching forms the backbone for most Visual Simultaneous Localization and Mapping (vSLAM), visual odometry, 3D reconstruction, and Structure from Motion (SfM) algorithms. However, recovering feature matche…
3D ReconstructionGraph Neural NetworkSimultaneous Localization and MappingVisual OdometryTightly-Coupled LiDAR-Visual SLAM Based on Geometric Features for Mobile Agents
The mobile robot relies on SLAM (Simultaneous Localization and Mapping) to provide autonomous navigation and task execution in complex and unknown environments. However, it is hard to develop a dedicated algorithm for mo…
Autonomous NavigationPose EstimationSimultaneous Localization and MappingVisual Odometry