mlsanityData to 7 Oct 2026

DyConfidMatch: Dynamic Thresholding and Re-sampling for 3D Semi-supervised Learning

arXiv 2411.08340 ↗First posted 13 Nov 2024cs.CVcited by 1

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Abstract (arXiv)

Semi-supervised learning (SSL) leverages limited labeled and abundant unlabeled data but often faces challenges with data imbalance, especially in 3D contexts. This study investigates class-level confidence as an indicator of learning status in 3D SSL, proposing a novel method that utilizes dynamic thresholding to better use unlabeled data, particularly from underrepresented classes. A re-sampling strategy is also introduced to mitigate bias towards well-represented classes, ensuring equitable class representation. Through extensive experiments in 3D SSL, our method surpasses state-of-the-art counterparts in classification and detection tasks, highlighting its effectiveness in tackling data imbalance. This approach presents a significant advancement in SSL for 3D datasets, providing a robust solution for data imbalance issues.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 33 of its 47 references that are in the map. First posted on arXiv 13 Nov 2024.

Builds on

33 of 47 references.

References · 33

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  2. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,080
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  9. 2019ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoringcited by 349
  10. 2020Rethinking the Value of Labels for Improving Class-Imbalanced Learningcited by 216
  11. 2021CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learningcited by 174
  12. 2021Dash: Semi-Supervised Learning with Dynamic Thresholdingcited by 147
21 more
  1. 2019SESS: Self-Ensembling Semi-Supervised 3D Object Detectioncited by 89
  2. 20203DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detectioncited by 89
  3. 2020DMT: Dynamic Mutual Training for Semi-Supervised Learningcited by 77
  4. 2022Semi-supervised 3D Object Detection with Proficient Teacherscited by 45
  5. 2022ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detectioncited by 43
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  13. 2023XVO: Generalized Visual Odometry via Cross-Modal Self-Trainingcited by 17
  14. 2023DQS3D: Densely-matched Quantization-aware Semi-supervised 3D Detectioncited by 16
  15. 2023Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detectioncited by 14
  16. 2024Event-guided Low-light Video Semantic Segmentationcited by 14
  17. 2021Advancing Self-supervised Monocular Depth Learning with Sparse LiDARcited by 13
  18. 2022Class-Level Confidence Based 3D Semi-Supervised Learningcited by 13
  19. 2024Detecting Misinformation in Multimedia Content through Cross-Modal Entity Consistency: A Dual Learning Approachcited by 12
  20. 2024Let Community Rules Be Reflected in Online Content Moderationcited by 9
  21. 2022Self-Supervised Leaf Segmentation under Complex Lighting Conditionscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Multi-Modal Decouple and Recouple Network for Robust 3D Object Detectioncited by 0