Papers Point Cloud Retrieval
“Point Cloud Retrieval” 태그가 달린 논문 18편 · 필터 해제
MorphoSkel3D: Morphological Skeletonization of 3D Point Clouds for Informed Sampling in Object Classification and Retrieval
Point clouds are a set of data points in space to represent the 3D geometry of objects. A fundamental step in the processing is to identify a subset of points to represent the shape. While traditional sampling methods of…
3D geometryPoint Cloud RetrievalPTC-Net: Point-Wise Transformer with Sparse Convolution Network for Place Recognition
In the point-cloud-based place recognition area, the existing hybrid architectures combining both convolutional networks and transformers have shown promising performance. They mainly apply the voxel-wise transformer aft…
Point Cloud RetrievalRetrievalSpectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization
In large-scale metric localization, an incorrect result during retrieval will lead to an incorrect pose estimate or loop closure. Re-ranking methods propose to take into account all the top retrieval candidates and re-or…
Point Cloud RegistrationPoint Cloud RetrievalPose EstimationRe-Ranking+1HiTPR: Hierarchical Transformer for Place Recognition in Point Cloud
Place recognition or loop closure detection is one of the core components in a full SLAM system. In this paper, aiming at strengthening the relevancy of local neighboring points and the contextual dependency among global…
Loop Closure DetectionPoint Cloud RetrievalImproving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training
The paper presents a simple and effective learning-based method for computing a discriminative 3D point cloud descriptor for place recognition purposes. Recent state-of-the-art methods have relatively complex architectur…
3D Place RecognitionImage RetrievalMetric LearningPoint Cloud Retrieval+2RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network
Point cloud-based large scale place recognition is an important but challenging task for many applications such as Simultaneous Localization and Mapping (SLAM). Taking the task as a point cloud retrieval problem, previou…
Autonomous DrivingPoint Cloud RetrievalRetrievalSimultaneous Localization and MappingTransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields
Place recognition plays an essential role in the field of autonomous driving and robot navigation. Point cloud based methods mainly focus on extracting global descriptors from local features of point clouds. Despite havi…
3D Place RecognitionAutonomous DrivingPoint Cloud RetrievalRobot NavigationSVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition
Point cloud-based large scale place recognition is fundamental for many applications like Simultaneous Localization and Mapping (SLAM). Although many models have been proposed and have achieved good performance by learni…
3D Place RecognitionPoint Cloud RetrievalSimultaneous Localization and MappingMinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
We introduce a discriminative multimodal descriptor based on a pair of sensor readings: a point cloud from a LiDAR and an image from an RGB camera. Our descriptor, named MinkLoc++, can be used for place recognition, re-l…
3D Place RecognitionAutonomous VehiclesMetric LearningMultimodal Deep Learning+2NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in lidar-based SLAM systems. This paper pr…
Autonomous DrivingLoop Closure DetectionPoint Cloud RetrievalRetrievalEfficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition
Point cloud based retrieval for place recognition is still a challenging problem due to drastic appearance and illumination changes of scenes in changing environments. Existing deep learning based global descriptors for …
Point Cloud RetrievalRetrievalVisual Place RecognitionPyramid Point Cloud Transformer for Large-Scale Place Recognition
Recently, deep learning based point cloud descriptors have achieved impressive results in the place recognition task. Nonetheless, due to the sparsity of point clouds, how to extract discriminative local features of …
3D Place RecognitionPoint Cloud RetrievalRetrievalSOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition
We tackle the problem of place recognition from point cloud data and introduce a self-attention and orientation encoding network (SOE-Net) that fully explores the relationship between points and incorporates long-range c…
3D Place RecognitionMetric LearningPoint Cloud RetrievalVisual Place RecognitionMinkLoc3D: Point Cloud Based Large-Scale Place Recognition
The paper presents a learning-based method for computing a discriminative 3D point cloud descriptor for place recognition purposes. Existing methods, such as PointNetVLAD, are based on unordered point cloud representatio…
3D Place RecognitionMetric LearningPoint Cloud RetrievalVisual Place RecognitionDH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization
For relocalization in large-scale point clouds, we propose the first approach that unifies global place recognition and local 6DoF pose refinement. To this end, we design a Siamese network that jointly learns 3D local fe…
3D Place RecognitionPoint Cloud RegistrationPoint Cloud RetrievalRetrievalPCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval
Point cloud based retrieval for place recognition is an emerging problem in vision field. The main challenge is how to find an efficient way to encode the local features into a discriminative global descriptor. In this p…
3D Place RecognitionPoint Cloud RetrievalRetrievalVisual Place RecognitionLPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dyna…
3D Place RecognitionPoint Cloud RetrievalRetrievalVisual Place RecognitionPointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
Unlike its image based counterpart, point cloud based retrieval for place recognition has remained as an unexplored and unsolved problem. This is largely due to the difficulty in extracting local feature descriptors from…
3D Place RecognitionPoint Cloud RetrievalRetrievalTriplet+2