mlsanityData to 14 Oct 2026

RWT-SLAM: Robust Visual SLAM for Highly Weak-textured Environments

arXiv 2207.03539 ↗First posted 7 Jul 2022cs.CVcited by 4

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Abstract (arXiv)

As a fundamental task for intelligent robots, visual SLAM has made great progress over the past decades. However, robust SLAM under highly weak-textured environments still remains very challenging. In this paper, we propose a novel visual SLAM system named RWT-SLAM to tackle this problem. We modify LoFTR network which is able to produce dense point matching under low-textured scenes to generate feature descriptors. To integrate the new features into the popular ORB-SLAM framework, we develop feature masks to filter out the unreliable features and employ KNN strategy to strengthen the matching robustness. We also retrained visual vocabulary upon new descriptors for efficient loop closing. The resulting RWT-SLAM is tested in various public datasets such as TUM and OpenLORIS, as well as our own data. The results shows very promising performance under highly weak-textured environments.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 25 of its 40 references that are in the map. First posted on arXiv 7 Jul 2022.

Builds on

25 of 40 references.

References · 25

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,443
  3. 2017SuperPoint: Self-Supervised Interest Point Detection and Descriptioncited by 1,320
  4. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 988
  5. 2021LoFTR: Detector-Free Local Feature Matching with Transformerscited by 984
  6. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 878
  7. 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 806
  8. 2016Direct Sparse Odometrycited by 485
  9. 2019R2D2: Repeatable and Reliable Detector and Descriptorcited by 207
  10. 2021COTR: Correspondence Transformer for Matching Across Imagescited by 183
  11. 2018Neighbourhood Consensus Networkscited by 174
  12. 2017CNN-SLAM: Real-time dense monocular SLAM with learned depth predictioncited by 152
13 more
  1. 2018CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAMcited by 152
  2. 2020ASLFeat: Learning Local Features of Accurate Shape and Localizationcited by 130
  3. 2020Learning Feature Descriptors using Camera Pose Supervisioncited by 104
  4. 2018DS-SLAM: A Semantic Visual SLAM towards Dynamic Environmentscited by 91
  5. 2020Dual-Resolution Correspondence Networkscited by 90
  6. 2018DeepTAM: Deep Tracking and Mappingcited by 87
  7. 2019ContextDesc: Local Descriptor Augmentation with Cross-Modality Contextcited by 79
  8. 2019Neural RGB->D Sensing: Depth and Uncertainty from a Video Cameracited by 69
  9. 2017PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segmentscited by 59
  10. 2019Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAMcited by 42
  11. 2020Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environmentscited by 22
  12. 2019GCNv2: Efficient Correspondence Prediction for Real-Time SLAMcited by 19
  13. 2020DXSLAM: A Robust and Efficient Visual SLAM System with Deep Featurescited by 17

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 0; 2026: 2.

4 papers.

  1. 2022Visual SLAM: What are the Current Trends and What to Expect?cited by 10
  2. 2024HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimationcited by 3
  3. 2026MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priorscited by 0
  4. 2026Does Dynamic-Point Filtering Help When Texture Is Scarce? A Controlled Study of ORB-SLAM2 Front-Ends in Synthetic Indoor Scenescited by 0