mlsanityData to 7 Oct 2026

Deep semi-supervised segmentation with weight-averaged consistency targets

arXiv 1807.04657 ↗First posted 12 Jul 2018cs.CVcited by 21

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Abstract (arXiv)

Recently proposed techniques for semi-supervised learning such as Temporal Ensembling and Mean Teacher have achieved state-of-the-art results in many important classification benchmarks. In this work, we expand the Mean Teacher approach to segmentation tasks and show that it can bring important improvements in a realistic small data regime using a publicly available multi-center dataset from the Magnetic Resonance Imaging (MRI) domain. We also devise a method to solve the problems that arise when using traditional data augmentation strategies for segmentation tasks on our new training scheme.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jul 2018.

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Citing papers per year: 2021: 11; 2022: 3; 2023: 5; 2024: 0; 2025: 2.

21 papers.

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  1. 2022Scribble-Supervised LiDAR Semantic Segmentationcited by 69
  2. 2021Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentationcited by 37
  3. 2021Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labelscited by 32
  4. 2021Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularizationcited by 14
  5. 2021Robust Mutual Learning for Semi-supervised Semantic Segmentationcited by 13
  6. 2021Label noise in segmentation networks : mitigation must deal with biascited by 10
  7. 2021Segmentation with mixed supervision: Confidence maximization helps knowledge distillationcited by 6
  8. 2022FixMatchSeg: Fixing FixMatch for Semi-Supervised Semantic Segmentationcited by 6
  9. 2021Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Meancited by 5
  10. 2023MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasetscited by 5
  11. 2023SPLAL: Similarity-based pseudo-labeling with alignment loss for semi-supervised medical image classificationcited by 4
  12. 2023GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labelscited by 4
9 more
  1. 2025Dual Cross-image Semantic Consistency with Self-aware Pseudo Labeling for Semi-supervised Medical Image Segmentationcited by 4
  2. 2021POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboringcited by 3
  3. 2023A Survey of Historical Learning: Learning Models with Learning Historycited by 3
  4. 2021Colour augmentation for improved semi-supervised semantic segmentationcited by 2
  5. 2022Boundary-aware Information Maximization for Self-supervised Medical Image Segmentationcited by 2
  6. 2023ContrasInver: Ultra-Sparse Label Semi-supervised Regression for Multi-dimensional Seismic Inversioncited by 1
  7. 2021Context-aware virtual adversarial training for anatomically-plausible segmentationcited by 0
  8. 2021Diversified Multi-prototype Representation for Semi-supervised Segmentationcited by 0
  9. 2025nnFilterMatch: A Unified Semi-Supervised Learning Framework with Uncertainty-Aware Pseudo-Label Filtering for Efficient Medical Segmentationcited by 0