【Review】用于SLAM的地点识别(Place Recognition)

目录

  • 1. Point Cloud(Lidar)
    • 2021
      • ICRA
      • ICCV
      • IROS
      • CVPR
      • Others
    • 2020
    • 2019
      • ICCV
    • 2018
      • IROS
  • 2. Researchers
  • 3. Visual
    • 2021
      • IROS
      • ICCV
      • CVPR
      • ICRA
    • 2020
      • CVPR
  • Reference:

1. Point Cloud(Lidar)

2021

ICRA

  1. NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
    (Paper, Github)
  2. DiSCO: Differentiable Scan Context with Orientation
    (paper, Github)
  3. Locus: LiDAR-Based Place Recognition Using Spatiotemporal Higher-Order Pooling
    (paper, Github)
  4. Robust Place Recognition Using an Imaging Lidar
    (paper, Github)

ICCV

  1. Pyramid Point Cloud Transformer for Large-Scale Place Recognition
    (Paper, Github)

IROS

  1. SSC: Semantic Scan Context for Large-Scale Place Recognition
    (Paper, Github)
  2. A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition
    (Paper, Github)
  3. Evaluation of Long-Term LiDAR Place Recognition

CVPR

  1. A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition
    ((Paper, Github))

Others

  1. MinkLoc3D: Point Cloud Based Large-Scale Place Recognition
    (WACV, paper, Github)
  2. MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions, spherical coordinates, and intensity
    (paper, Github)

2020

2019

ICCV

  1. LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
    (Paper, Github)

2018

IROS

  1. Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition
    (Paper, Github)
  2. Scan Context: Egocentric Spatial Descriptor for Place Recognition within {3D} Point Cloud Map
    (Paper, Github)

2. Researchers

  1. Peng Yin
    Carnegie Mellon University | CMU · Robotics Institute
  2. Ji Zhang
    Carnegie Mellon University | CMU · Robotics Institute
  3. Giseop Kim
    Korea Advanced Institute of Science and Technology | KAIST · Department of Civil and Environmental Engineering
  4. Lin Li
    Zhejiang University | ZJU · Department of Control Science and Engineering

3. Visual

2021

IROS

  1. A Hierarchical Dual Model of Environment- and Place-Specific Utility for Visual Place Recognition
    (Paper, Github)
  2. Visual Place Recognition using LiDAR Intensity Information
    (Paper, Github)
  3. SymbioLCD: Ensemble-Based Loop Closure Detection using CNN-Extracted Objects and Visual Bag-of-Words
    (Paper, Github)
  4. Visual Place Recognition Using LiDAR Intensity Information
    (Paper, Github)

ICCV

  1. Conformer: Local Features Coupling Global Representations for Visual Recognition
    (Paper, Github)
  2. Attentional Pyramid Pooling of Salient Visual Residuals for Place Recognition
    (Paper, Github)

CVPR

  1. OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
    (Paper, Github)
  2. Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
    (Paper, Github)

ICRA

  1. Intelligent Reference Curation for Visual Place Recognition Via Bayesian Selective Fusion
    (Paper, Github)
  2. Appearance-Based Loop Closure Detection Via Bidirectional Manifold Representation Consensus
  3. SoftMP: Attentive Feature Pooling for Joint Local Feature Detection and Description for Place Recognition in Changing Environments
  4. Simultaneous Multi-Level Descriptor Learning and Semantic Segmentation for Domain-Specific Relocalization
  5. Resolving Place Recognition Inconsistencies Using Intra-Set Similarities
  6. Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems
    (Paper, Github)
  7. Retrieval and Localization with Observation Constraints
  8. A Flexible and Efficient Loop Closure Detection Based on Motion Knowledge
  9. Semantic Reinforced Attention Learning for Visual Place Recognition
  10. STA-VPR: Spatio-Temporal Alignment for Visual Place Recognition
    (Paper, Github)
  11. Visual Place Recognition Via Local Affine Preserving Matching

2020

CVPR

  1. SuperGlue: Learning Feature Matching with Graph Neural Networks
    (Paper, Github)
  2. CORAL Colored Structural Representation for Bi-Modal Place Recognition
    (Paper, Github)

Reference:

  1. ICRA2021 SLAM方向论文汇总
  2. IROS2021 SLAM方向论文汇总
  3. CVPR 2021 SLAM 相关论文汇总
  4. ICCV2021 SLAM 点云配准 深度估计 自动驾驶等文章汇总

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