Research map / Detection and segmentation / Weakly supervised detection and segmentation
Consistency regularization for segmentation
Use weak-to-strong and multi-scale consistency for semi-supervised semantic segmentation.
25 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2018–2025) · an approach in Weakly supervised detection and segmentation, keyword cluster “semi supervised · pseudo · unlabeled”
State History Tried Checklist Preprints Who Export
Where it stands
Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.
11 papers in 2023–24 and 4 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 9.6% to 5.6%.
How this is decided
A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.
How it got here
Most cited paper of each year
- 2018 · Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer (CVPR 2018 · 129 citations)
- 2019 · Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images (CVPR 2019 · 297 citations)
- 2020 · Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks (CVPR 2020 · 103 citations)
- 2021 · Semi-Supervised Semantic Segmentation With Directional Context-Aware Consistency (CVPR 2021 · 245 citations)
- 2022 · Tree Energy Loss: Towards Sparsely Annotated Semantic Segmentation (CVPR 2022 · 83 citations)
- 2023 · Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation (CVPR 2023 · 565 citations)
- 2024 · CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation (CVPR 2024 · 94 citations)
- 2025 · SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image Segmentation (AAAI 2025 · 8 citations)
Earliest papers here
- Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer (CVPR 2018 · 129 citations)
- Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images (CVPR 2019 · 297 citations)
- Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks (CVPR 2020 · 103 citations)
What has been tried
24 papers here report 299 measured changes (a component added, removed or swapped, compared with a baseline): helped 75%, no clear effect 4%, hurt 19%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.
Ablations in recent papers
| What was changed | Measured on | Result | Effect | Paper |
|---|---|---|---|---|
| Add pixel propagation to the no-propagation method | Pascal VOC 2012 val, original 92-label split · mIoU (%) | 74.4 -> 75.8 | Helped | CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation (CVPR 2024 · 94 citations) |
| add contrastive learning | PASCAL classic 1/16 (92) · mIoU | 67.4 -> 68.6 | Helped | RankMatch: Exploring the Better Consistency Regularization for Semi-supervised Semantic Segmentation (CVPR 2024 · 63 citations) |
| Add channel-wise cross-attention (CCA) to the pseudo-labeling baseline | PASCAL 1/8 (183) · mIoU | 68.71 -> 76.77 | Helped | AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation (CVPR 2024 · 55 citations) |
| Add SGAL to a model without SGAL or TVDT | KiTS19, 9 labeled volumes · Dice | 0.780 -> 0.892 | Helped | SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image Segmentation (AAAI 2025 · 8 citations) |
| add image-level scale variation consistency (ISVC) | PASCAL Original 1/4 and 1/2 · mIoU | 75.78 -> 78.72; 77.89 -> 81.06 | Helped | ScaleMatch: Multi-scale Consistency Enhancement for Semi-supervised Semantic Segmentation (AAAI 2025 · 7 citations) |
| Add FPA | BUSI 1/4 · Dice | 71.49±2.27 -> 76.20±2.73 | Helped | CSC-PA: Cross-image Semantic Correlation via Prototype Attentions for Single-network Semi-supervised Breast Tumor Segmentation (CVPR 2025 · 4 citations) |
| add Pre-trained Unsupervised Classification (PUC) | ShanghaiWaste-Seg · mIoU | 36.4 -> 38.4(+2.0) | Helped | WISNet: Pseudo Label Generation on Unbalanced and Patch Annotated Waste Images (CVPR 2025 · 2 citations) |
| Add look-ahead acquisition | PASCAL, 5K budget · Model mIoU | 56.82 (± 0.05) -> 68.72 (± 0.10) | Helped | Active Label Correction for Semantic Segmentation with Foundation Models (ICML 2024 · 0 citations) |
What reviewers will expect
Datasets and baselines named in the 9 papers of this approach from 2024–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.
Datasets
- PASCAL VOC 2012 · 5 of 9 papers
- Cityscapes · 5 of 9 papers
Baselines
- UniMatch · 5 of 9 papers
- AugSeg · 5 of 9 papers
- U2PL · 5 of 9 papers
- CPS · 4 of 9 papers
- ST++ · 3 of 9 papers
- ESL · 3 of 9 papers
- CCVC · 3 of 9 papers
- CorrMatch · 2 of 9 papers
Recent preprints
Loading recent arXiv preprints…
Who publishes on it
Institutions on the most papers of this approach since 2023 (of 15 papers; from OpenAlex and the papers' affiliations).
- Shenzhen University · 2 papers
- Wuhan University · 2 papers
- SenseTime · 2 papers
- Hong Kong University of Science and Technology · 2 papers
- Pohang University of Science and Technology · 2 papers
Use it
Download BibTeX of 23 key papersOpen the topic in the interactive map
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Related approaches
Same keyword cluster
- Pseudo-labeling for semi-supervised detection (76 papers)
- Semi-supervised instance segmentation (16 papers)
Elsewhere in the topic
- Weakly supervised semantic segmentation (116 papers)
- Weakly supervised detection (97 papers)
- Weakly supervised object localization (54 papers)
- CAM refinement and prototypes (52 papers)
Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).