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3D Place Recognition
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Pointcloud-based place recognition and retrieval
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
RE-TRIP : Reflectivity Instance Augmented Triangle Descriptor for 3D Place Recognition
Place Recognition: A Comprehensive Review, Current Challenges and Future Directions
HOTFormerLoc: Hierarchical Octree Transformer for Versatile Lidar Place Recognition Across Ground and Aerial Views
ForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density Images
Fast 3D point clouds retrieval for Large-scale 3D Place Recognition
SPVSoAP3D: A Second-order Average Pooling Approach to enhance 3D Place Recognition in Horticultural Environments
SALSA: Swift Adaptive Lightweight Self-Attention for Enhanced LiDAR Place Recognition
TReR: A Lightweight Transformer Re-Ranking Approach for 3D LiDAR Place Recognition
CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition
STD: Stable Triangle Descriptor for 3D place recognition
SphereVLAD++: Attention-based and Signal-enhanced Viewpoint Invariant Descriptor
0/1 Deep Neural Networks via Block Coordinate Descent
Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions, spherical coordinates, and intensity
LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition
TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields
SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition
MinkLoc3D: Point Cloud Based Large-Scale Place Recognition
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization
PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval
LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.