8.6.4.10 Semi-Supervised Semantic Segmentation

Song, Y., Ou, Z.,
Semi-Supervised Seq2seq Joint-Stochastic-Approximation Autoencoders With Applications to Semantic Parsing,
SPLetters(27), 2020, pp. 31-35.
IEEE DOI 2001
Semi-supervised learning, seq2seq, semantic parsing, joint stochastic approximation, variational auto-encoder BibRef

Liang, C.B.[Chen-Bin], Cheng, B.[Bo], Xiao, B.H.[Bai-Hua], He, C.Q.[Chenlin-Qiu], Liu, X.N.[Xu-Nan], Jia, N.[Ning], Chen, J.F.[Jin-Fen],
Semi-/Weakly-Supervised Semantic Segmentation Method and Its Application for Coastal Aquaculture Areas Based on Multi-Source Remote Sensing Images: Taking the Fujian Coastal Area (Mainly Sanduo) as an Example,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Hu, P.[Ping], Sclaroff, S.[Stan], Saenko, K.[Kate],
Leveraging Geometric Structure for Label-Efficient Semi-Supervised Scene Segmentation,
IP(31), 2022, pp. 6320-6330.
IEEE DOI 2210
Annotations, Training, Labeling, Solid modeling, Task analysis, Semantics, Semantic segmentation, geometric structure BibRef

Guo, X.Q.[Xiao-Qing], Liu, J.[Jie], Yuan, Y.X.[Yi-Xuan],
Semantic-Oriented Labeled-to-Unlabeled Distribution Translation for Image Segmentation,
MedImg(41), No. 2, February 2022, pp. 434-445.
IEEE DOI 2202
Code, Segmentation.
WWW Link. Image segmentation, Semantics, Feature extraction, Data models, Task analysis, Semisupervised learning, few sample segmentation BibRef

Guo, X.Q.[Xiao-Qing], Yang, C.[Chen], Li, B.[Baopu], Yuan, Y.X.[Yi-Xuan],
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation,
CVPR21(3926-3935)
IEEE DOI 2111
Bridges, Adaptation models, Computational modeling, Semantics, Estimation, Metadata BibRef

Cao, C.[Cong], Lin, T.W.[Tian-Wei], He, D.L.[Dong-Liang], Li, F.[Fu], Yue, H.J.[Huan-Jing], Yang, J.Y.[Jing-Yu], Ding, E.[Errui],
Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation,
CirSysVideo(33), No. 2, February 2023, pp. 793-803.
IEEE DOI 2302
Semantics, Image segmentation, Training, Perturbation methods, Data models, Context modeling, Task analysis, differentiable spatial warping BibRef

Kim, S.[Soopil], Chikontwe, P.[Philip], An, S.[Sion], Park, S.H.[Sang Hyun],
Uncertainty-aware semi-supervised few shot segmentation,
PR(137), 2023, pp. 109292.
Elsevier DOI 2302
Few shot segmentation, Meta learning, Uncertainty estimation, Semi-supervised learning, Prototype BibRef

Zang, Y.H.[Yu-Hang], Zhou, K.Y.[Kai-Yang], Huang, C.[Chen], Loy, C.C.[Chen Change],
Semi-Supervised and Long-Tailed Object Detection with CascadeMatch,
IJCV(131), No. 1, January 2023, pp. 987-1001.
Springer DOI 2303
BibRef

Chen, J.K.[Jing-Kun], Zhang, J.G.[Jian-Guo], Debattista, K.[Kurt], Han, J.G.[Jun-Gong],
Semi-Supervised Unpaired Medical Image Segmentation Through Task-Affinity Consistency,
MedImg(42), No. 3, March 2023, pp. 594-605.
IEEE DOI 2303
Image segmentation, Task analysis, Feature extraction, Training, Semisupervised learning, Medical diagnostic imaging, consistency BibRef

Wu, F.P.[Fu-Ping], Zhuang, X.H.[Xia-Hai],
Minimizing Estimated Risks on Unlabeled Data: A New Formulation for Semi-Supervised Medical Image Segmentation,
PAMI(45), No. 5, May 2023, pp. 6021-6036.
IEEE DOI 2304
Image segmentation, Training, Biomedical imaging, Task analysis, Data models, Minimization, Risk management, Semi-supervised learning BibRef

Wu, L.S.[Lin-Shan], Fang, L.Y.[Le-Yuan], He, X.X.[Xing-Xin], He, M.[Min], Ma, J.Y.[Jia-Yi], Zhong, Z.[Zhun],
Querying Labeled for Unlabeled: Cross-Image Semantic Consistency Guided Semi-Supervised Semantic Segmentation,
PAMI(45), No. 7, July 2023, pp. 8827-8844.
IEEE DOI 2306
Semantics, Semantic segmentation, Reliability, Training, Task analysis, Annotations, Deep learning, semi-supervised learning BibRef

Gu, R.[Ran], Zhang, J.Y.[Jing-Yang], Wang, G.[Guotai], Lei, W.H.[Wen-Hui], Song, T.[Tao], Zhang, X.F.[Xiao-Fan], Li, K.[Kang], Zhang, S.T.[Shao-Ting],
Contrastive Semi-Supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures,
MedImg(42), No. 1, January 2023, pp. 245-256.
IEEE DOI 2301
Image segmentation, Annotations, Adaptation models, Training, Biomedical imaging, Anatomical structure, Task analysis, contrastive learning BibRef

Dang, B.[Bo], Li, Y.S.[Yan-Sheng], Zhang, Y.J.[Yong-Jun], Ma, J.Y.[Jia-Yi],
Progressive Learning With Cross-Window Consistency for Semi-Supervised Semantic Segmentation,
IP(33), 2024, pp. 5219-5231.
IEEE DOI Code:
HTML Version. 2410
Semantic segmentation, Semantics, Data models, Pipelines, Visualization, Remote sensing, Medical diagnostic imaging, pseudo-label supervision BibRef

Wang, Y.[Ying], Xuan, Z.W.[Zi-Wei], Ho, C.[Chiuman], Qi, G.J.[Guo-Jun],
Adversarial Dense Contrastive Learning for Semi-Supervised Semantic Segmentation,
IP(32), 2023, pp. 4459-4471.
IEEE DOI 2309
BibRef

Lee, M.[Minhyun], Lee, S.[Seungho], Lee, J.[Jongwuk], Shim, H.J.[Hyun-Jung],
Saliency as Pseudo-Pixel Supervision for Weakly and Semi-Supervised Semantic Segmentation,
PAMI(45), No. 10, October 2023, pp. 12341-12357.
IEEE DOI 2310
BibRef

Lee, S.[Seungho], Lee, M.[Minhyun], Lee, J.[Jongwuk], Shim, H.J.[Hyun-Jung],
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation,
CVPR21(5491-5501)
IEEE DOI 2111
Location awareness, Training, Image segmentation, Codes, Semantics, Pattern recognition BibRef

Hou, Y.Z.[Yun-Zhong], Gould, S.[Stephen], Zheng, L.[Liang],
View-coherent correlation consistency for semi-supervised semantic segmentation,
PR(147), 2024, pp. 110089.
Elsevier DOI 2312
Semi-supervised learning, Semantic segmentation, Contrastive learning, Data augmentation BibRef

Chen, Z.J.[Ze-Jian], Zhuo, W.[Wei], Wang, T.F.[Tian-Fu], Cheng, J.[Jun], Xue, W.F.[Wu-Feng], Ni, D.[Dong],
Semi-Supervised Representation Learning for Segmentation on Medical Volumes and Sequences,
MedImg(42), No. 12, December 2023, pp. 3972-3986.
IEEE DOI Code:
WWW Link. 2312
BibRef

Wu, J.W.[Jia-Wei], Fan, H.Y.[Hao-Yi], Li, Z.Y.[Zuo-Yong], Liu, G.H.[Guang-Hai], Lin, S.[Shouying],
Information Transfer in Semi-Supervised Semantic Segmentation,
CirSysVideo(34), No. 2, February 2024, pp. 1174-1185.
IEEE DOI 2402
Semantic segmentation, Training, Task analysis, Semantics, Bars, Semisupervised learning, Entropy, Semi-supervised learning, information transfer BibRef

Wang, Y.S.[Yoo-Seung], Jang, J.[Jaehyuk], Kim, C.[Changick],
Subdivided Mask Dispersion Framework for Semi-Supervised Semantic Segmentation,
PRL(179), 2024, pp. 58-64.
Elsevier DOI 2403
Semi-supervised semantic segmentation, Semi-supervised learning, Cutmix, Transformer BibRef

Miao, J.Z.[Ju-Zheng], Zhou, S.P.[Si-Ping], Zhou, G.Q.[Guang-Quan], Wang, K.N.[Kai-Ni], Yang, M.[Meng], Zhou, S.[Shoujun], Chen, Y.[Yang],
SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation,
MedImg(43), No. 4, April 2024, pp. 1347-1364.
IEEE DOI 2404
Image segmentation, Biomedical imaging, Reliability, Task analysis, Training, Semisupervised learning, Semantics, Self-correcting, structure constraint BibRef

Zhang, F.[Fan], Liu, H.Y.[Hui-Ying], Wang, J.J.[Jin-Jiang], Lyu, J.[Jun], Cai, Q.[Qing], Li, H.F.[Hua-Feng], Dong, J.Y.[Jun-Yu], Zhang, D.[David],
Cross Co-Teaching for Semi-Supervised Medical Image Segmentation,
PR(152), 2024, pp. 110426.
Elsevier DOI 2405
Semi-supervised medical image segmentation, Signed distance function, Interactive lateral fusion mechanism BibRef

Wu, Q.H.[Qian-Hao], Jiang, X.X.[Xi-Xi], Zhang, D.[Dong], Feng, Y.F.[Yi-Fei], Tang, J.H.[Jin-Hui],
Cross-Set Data Augmentation for Semi-Supervised Medical Image Segmentation,
IVC(154), 2025, pp. 105407.
Elsevier DOI 2502
Semi-supervised learning, Medical image segmentation, Cross-set data augmentation, Distribution alignment BibRef

Zhang, R.T.[Run-Tong], Zhu, H.Y.[Hong-Yuan], Zhang, H.W.[Han-Wang], Gong, C.[Chen], Zhou, J.T.Y.[Joey Tian-Yi], Meng, F.M.[Fan-Man],
Blessing few-shot segmentation via semi-supervised learning with noisy support images,
PR(154), 2024, pp. 110503.
Elsevier DOI 2406
Few-shot segmentation, Semi-supervised learning, Noisy images, Causal inference BibRef

Zhang, R.T.[Run-Tong], Zhu, H.Y.[Hong-Yuan], Zhang, H.W.[Han-Wang], Gong, C.[Chen], Zhou, J.T.Y.[Joey Tian-Yi], Meng, F.M.[Fan-Man],
Semi-Supervised Few-Shot Segmentation with Noisy Support Images,
ICIP23(1550-1554)
IEEE DOI 2312
BibRef

Xiao, H.[Hui], Hong, Y.T.[Yu-Ting], Dong, L.[Li], Yan, D.[Diqun], Xiong, J.J.[Jun-Jie], Zhuang, J.Y.[Jia-Yan], Liang, D.[Dongtai], Peng, C.B.[Cheng-Bin],
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-Supervised Semantic Segmentation,
MultMed(26), 2024, pp. 8077-8087.
IEEE DOI 2408
Semantic segmentation, Noise measurement, Semantics, Data models, Training, Semisupervised learning, Predictive models, graph convolution BibRef

Xie, H.Y.[Hao-Yu], Wang, C.Q.[Chang-Qi], Zhao, J.[Jian], Liu, Y.[Yang], Dan, J.[Jun], Fu, C.[Chong], Sun, B.G.[Bai-Gui],
PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation,
IJCV(132), No. 10, October 2024, pp. 4343-4361.
Springer DOI 2410
BibRef

Yin, J.J.[Jian-Jian], Yan, S.[Shuai], Chen, T.[Tao], Chen, Y.[Yi], Yao, Y.Z.[Ya-Zhou],
Class Probability Space Regularization for semi-supervised semantic segmentation,
CVIU(249), 2024, pp. 104146.
Elsevier DOI Code:
WWW Link. 2412
Human visual attention mechanisms, Semi-supervised semantic segmentation, Tail probability suppression BibRef

Wang, J.H.[Jia-Hui], Ruan, D.S.[Dong-Sheng], Li, Y.[Yang], Wang, Z.F.[Ze-Feng], Wu, Y.Q.[Yong-Quan], Tan, T.[Tao], Yang, G.[Guang], Jiang, M.F.[Ming-Feng],
Data augmentation strategies for semi-supervised medical image segmentation,
PR(159), 2025, pp. 111116.
Elsevier DOI Code:
WWW Link. 2412
Semi-supervised segmentation, Cropping and stitching, Laplace pyramid fusion, Mutual consistency BibRef

Yang, X.[Xi], Zhou, Q.[Qiubai], Wei, Z.Y.[Zi-Yu], Liu, H.[Hong], Wang, N.N.[Nan-Nan], Gao, X.B.[Xin-Bo],
Elaborate Teacher: Improved Semi-Supervised Object Detection With Rich Image Exploiting,
MultMed(26), 2024, pp. 11345-11357.
IEEE DOI 2412
Object detection, Data augmentation, Data models, Semantics, Task analysis, Predictive models, Semisupervised learning, teacher-student framework BibRef

Zeng, Q.J.[Qing-Jie], Xie, Y.T.[Yu-Tong], Lu, Z.[Zilin], Lu, M.K.[Meng-Kang], Zhang, J.F.[Jing-Feng], Xia, Y.[Yong],
Consistency-Guided Differential Decoding for Enhancing Semi-Supervised Medical Image Segmentation,
MedImg(44), No. 1, January 2025, pp. 44-56.
IEEE DOI Code:
WWW Link. 2501
Decoding, Image segmentation, Training, Semisupervised learning, Task analysis, Medical diagnostic imaging, Labeling, differential feature learning BibRef

Zeng, Q.J.[Qing-Jie], Xie, Y.T.[Yu-Tong], Lu, Z.[Zilin], Lu, M.K.[Meng-Kang], Wu, Y.C.[Yi-Cheng], Xia, Y.[Yong],
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation,
MedImg(44), No. 7, July 2025, pp. 2948-2959.
IEEE DOI Code:
WWW Link. 2507
Data models, Training, Image segmentation, Biomedical imaging, Head, Spleen, Data mining, Annotations, Adaptation models, unified learning BibRef

Zeng, Q.J.[Qing-Jie], Lu, Z.L.[Zi-Lin], Xie, Y.T.[Yu-Tong], Xia, Y.[Yong],
PICK: Predict and Mask for Semi-supervised Medical Image Segmentation,
IJCV(133), No. 6, June 2025, pp. Psges 3296-3311.
Springer DOI 2505
BibRef

Han, W.Q.[Wen-Qi], Jiang, W.[Wen], Geng, J.[Jie], Miao, W.[Wang],
Difference-Complementary Learning and Label Reassignment for Multimodal Semi-Supervised Semantic Segmentation of Remote Sensing Images,
IP(34), 2025, pp. 566-580.
IEEE DOI 2501
Remote sensing, Optical sensors, Semantic segmentation, Optical imaging, Radar polarimetry, Adaptive optics, remote sensing BibRef

Hu, K.[Kai], Chen, X.B.[Xiao-Bo], Chen, Z.N.[Zhi-Neng], Zhang, Y.[Yuan], Gao, X.[Xieping],
Multi-Perspective Pseudo-Label Generation and Confidence-Weighted Training for Semi-Supervised Semantic Segmentation,
MultMed(27), 2025, pp. 300-311.
IEEE DOI 2501
Training, Semantic segmentation, Predictive models, Data models, Perturbation methods, Semantics, Semisupervised learning, semantic segmentation BibRef

Liu, Y.Y.[Yu-Yuan], Tian, Y.[Yu], Wang, C.[Chong], Chen, Y.H.[Yuan-Hong], Liu, F.B.[Feng-Bei], Belagiannis, V.[Vasileios], Carneiro, G.[Gustavo],
Translation Consistent Semi-Supervised Segmentation for 3D Medical Images,
MedImg(44), No. 2, February 2025, pp. 952-968.
IEEE DOI Code:
WWW Link. 2502
Training, Image segmentation, Perturbation methods, Data models, Computational modeling, Predictive models, Benchmark testing, semi-supervised learning BibRef

Qiao, P.C.[Peng-Chong], Wang, Y.[Yu], Liu, C.[Chang], Shang, L.[Lei], Sun, B.G.[Bai-Gui], Wang, Z.N.[Zhen-Nan], Zheng, X.W.[Xia-Wu], Ji, R.R.[Rong-Rong], Chen, J.[Jie],
Adaptive Fuzzy Positive Learning for Annotation-Scarce Semantic Segmentation,
IJCV(133), No. 3, March 2025, pp. 1048-1066.
Springer DOI 2502
BibRef

Qiao, P.C.[Peng-Chong], Wei, Z.D.[Zhi-Dan], Wang, Y.[Yu], Wang, Z.N.[Zhen-Nan], Song, G.[Guoli], Xu, F.[Fan], Ji, X.Y.[Xiang-Yang], Liu, C.[Chang], Chen, J.[Jie],
Fuzzy Positive Learning for Semi-Supervised Semantic Segmentation,
CVPR23(15465-15474)
IEEE DOI 2309
BibRef

Zhang, R.X.[Rui-Xiang], Xu, C.[Chang], Xu, F.[Fang], Yang, W.[Wen], He, G.J.[Guang-Jun], Yu, H.[Huai], Xia, G.S.[Gui-Song],
S3OD: Size-unbiased semi-supervised object detection in aerial images,
PandRS(221), 2025, pp. 179-192.
Elsevier DOI Code:
WWW Link. 2503
Aerial images, Semi-supervised learning, Object detection BibRef

Yang, L.[Lihe], Zhao, Z.[Zhen], Zhao, H.S.[Heng-Shuang],
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation,
PAMI(47), No. 4, April 2025, pp. 3031-3048.
IEEE DOI 2503
Training, Semantic segmentation, Pipelines, Predictive models, Benchmark testing, Annotations, Visualization, Transformers, vision transformer BibRef

Wang, H.C.[Hao-Chen], Wang, Y.C.[Yu-Chao], Shen, Y.J.[Yu-Jun], Fan, J.S.[Jun-Song], Wang, Y.X.[Yu-Xi], Zhang, Z.X.[Zhao-Xiang],
Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation,
IJCV(133), No. 4, April 2025, pp. 1476-1498.
Springer DOI 2504
BibRef

Wang, Y.C.[Yu-Chao], Wang, H.C.[Hao-Chen], Shen, Y.J.[Yu-Jun], Fei, J.J.[Jing-Jing], Li, W.[Wei], Jin, G.Q.[Guo-Qiang], Wu, L.W.[Li-Wei], Zhao, R.[Rui], Le, X.[Xinyi],
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels,
CVPR22(4238-4247)
IEEE DOI 2210
Training, Visualization, Shape, Semantics, Predictive models, Semisupervised learning, Solids, Segmentation, Self- semi- meta- unsupervised learning BibRef

Ran, L.Y.[Ling-Yan], Li, Y.[Yali], Liang, G.Q.[Guo-Qiang], Zhang, Y.N.[Yan-Ning],
Pseudo Labeling Methods for Semi-Supervised Semantic Segmentation: A Review and Future Perspectives,
CirSysVideo(35), No. 4, April 2025, pp. 3054-3080.
IEEE DOI 2504
Training, Data models, Semantic segmentation, Reviews, Deep learning, Computational modeling, semi-supervised learning BibRef

Zhang, D.K.[Deng-Ke], Tang, Q.[Quan], Liu, F.G.[Fa-Gui], Mei, H.Q.[Hai-Qing], Chen, C.L.P.[C. L. Philip],
Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation,
SPLetters(32), 2025, pp. 1885-1889.
IEEE DOI 2505
Training, Decoding, Computational modeling, Data models, Semantic segmentation, Transformers, Predictive models, vision transformer BibRef

Ma, Q.K.[Qian-Kun], Zhang, Z.[Ziyao], Qiao, P.C.[Peng-Chong], Wang, Y.[Yu], Ji, R.R.[Rong-Rong], Liu, C.[Chang], Chen, J.[Jie],
Dual-Level Masked Semantic Inference for Semi-Supervised Semantic Segmentation,
MultMed(27), 2025, pp. 4029-4042.
IEEE DOI 2507
Semantics, Semantic segmentation, Context modeling, Data models, Training, Perturbation methods, Computational modeling, semi-supervised learning BibRef

Du, G.X.[Guang-Xing], Wu, R.[Rui], Xu, J.M.[Jin-Ming], Zeng, X.[Xiang], Xiong, S.W.[Sheng-Wu],
Dual Diversity and Pseudo-Label Correction Learning for Semi-Supervised Medical Image Segmentation,
IJIST(35), No. 5, 2025, pp. e70194.
DOI Link Code:
WWW Link. 2509
co-training, medical image segmentation, pseudo-labeling, semi-supervised learning BibRef

Zeng, X.[Xiang], Xiong, S.W.[Sheng-Wu], Xu, J.M.[Jin-Ming], Du, G.X.[Guang-Xing], Rong, Y.[Yi],
Uncertainty Co-Estimator for Improving Semi-Supervised Medical Image Segmentation,
MedImg(44), No. 9, September 2025, pp. 3870-3881.
IEEE DOI Code:
WWW Link. 2510
Uncertainty, Image segmentation, Predictive models, Estimation, Training, Perturbation methods, Artificial intelligence, Noise, uncertainty estimation BibRef

Guo, X.R.[Xiu-Rui], Lu, Y.[Yu], Zuo, Y.[Yang], Wang, J.X.[Jun-Xia], Zheng, Y.J.[Yuan-Jie],
IEDC-Net: Internal-External Dual Correction Mechanisms for Semi-Supervised Medical Image Segmentation,
IJIST(35), No. 5, 2025, pp. e70163.
DOI Link 2509
medical image segmentation, multi-model architecture, mutual consistency, semi-supervised learning, uncertainty estimation BibRef

Yu, B.Q.[Bao-Qi], Liu, Y.[Yong],
Caudo-Diff: Diffusion calibrated pseudo labels in guided latent space for minimally supervised medical segmentation,
PR(170), 2026, pp. 112007.
Elsevier DOI 2509
Diffusion model, Medical image segmentation, Minimally supervised learning, Pseudo label BibRef

Huang, Y.[Yigeng], Li, S.[Suwen], Guo, Z.[Zheng], Mei, Q.[Qiao], Han, Z.[Zhuo], Wang, X.J.[Xiu-Juan], Wang, H.Q.[Huan-Qin],
Boundary feature alignment for semi-supervised medical image segmentation,
PR(170), 2026, pp. 111946.
Elsevier DOI Code:
WWW Link. 2509
Semi-supervised medical image segmentation, Boundary learning, Feature alignment BibRef

Sun, W.J.[Wen-Jie], Lei, Y.J.[Yu-Jie], Hong, D.F.[Dan-Feng], Hu, Z.W.[Zhong-Wen], Li, Q.Q.[Qing-Quan], Zhang, J.[Jie],
RSProtoSemiSeg: Semi-supervised semantic segmentation of high spatial resolution remote sensing images with probabilistic distribution prototypes,
PandRS(228), 2025, pp. 771-784.
Elsevier DOI Code:
WWW Link. 2509
Remote sensing, Semi-supervised semantic segmentation, Distribution prototypes, Probabilistic embedding, Contrastive learning BibRef

Yin, J.J.[Jian-Jian], Chen, T.[Tao], Pei, G.S.[Gen-Sheng], Liu, H.F.[Hua-Feng], Yao, Y.Z.[Ya-Zhou], Nie, L.Q.[Li-Qiang], Hua, X.S.[Xian-Sheng],
Semi-Supervised Semantic Segmentation with Multi-Constraint Consistency Learning,
MultMed(27), 2025, pp. 6449-6461.
IEEE DOI 2510
Decoding, Semantic segmentation, Training, IP networks, Feature extraction, Data mining, Semantics, Prototypes, Noise, self-adaptive intervention
See also Graph-Based Semi-Supervised Learning with Multiple Labels. BibRef

Li, S.[Shiman], Zhao, J.[Jiayue], Hao, Y.[Yi], Zhang, C.X.[Chen-Xi], Song, Z.J.[Zhi-Jian],
Beyond the Distribution: Perturbation Toward Domain Distribution Boundary for Strengthening Generalizable Semi-Supervised Segmentation,
SPLetters(32), 2025, pp. 3535-3539.
IEEE DOI 2510
Perturbation methods, Biomedical imaging, Computational modeling, Data models, Training, Magnetic resonance imaging, boundary perturbation BibRef

Lu, C.Y.[Chen-Yi], Derakhshandeh, K.[Kasra], Chaterji, S.[Somali],
Improving Semi-Supervised Semantic Segmentation with Sliced-Wasserstein Feature Alignment and Uniformity,
CVPR25(20233-20243)
IEEE DOI 2508
Training, Measurement, Monte Carlo methods, Accuracy, Semantic segmentation, Semisupervised learning, Optimization BibRef

Karypidis, E.[Efstathios], Kakogeorgiou, I.[Ioannis], Gidaris, S.[Spyros], Komodakis, N.[Nikos],
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers,
CVPR25(3793-3803)
IEEE DOI Code:
WWW Link. 2508
Training, Visualization, Accuracy, Computational modeling, Semantic segmentation, Semantics, Pipelines, Predictive models, masked visual modeling BibRef

Ma, Q.[Qinghe], Zhang, J.[Jian], Li, Z.K.[Ze-Kun], Qi, L.[Lei], Yu, Q.[Qian], Shi, Y.H.[Ying-Huan],
Steady Progress Beats Stagnation: Mutual Aid of Foundation and Conventional Models in Mixed Domain Semi-Supervised Medical Image Segmentation,
CVPR25(5175-5185)
IEEE DOI Code:
WWW Link. 2508
Training, Image segmentation, Visualization, Foundation models, Reliability, Optimization, Convergence, Biomedical imaging, domain shift BibRef

Hu, M.[Ming], Yin, J.[Jianfu], Ma, Z.Z.[Zhuang-Zhuang], Ma, J.H.[Jian-Heng], Zhu, F.Y.[Fei-Yu], Wu, B.B.[Bing-Bing], Wen, Y.[Ya], Wu, M.[Meng], Hu, C.[Cong], Hu, B.L.[Bing-Liang], Wang, Q.[Quan],
beta-FFT: Nonlinear Interpolation and Differentiated Training Strategies for Semi-Supervised Medical Image Segmentation,
CVPR25(30839-30849)
IEEE DOI Code:
WWW Link. 2508
Training, Interpolation, Image segmentation, Fast Fourier transforms, System performance, Data processing, deep co-training BibRef

Assefa, M.[Maregu], Naseer, M.[Muzammal], Ganapathi, I.I.[Iyyakutti Iyappan], Ali, S.S.[Syed Sadaf], Seghier, M.L.[Mohamed L], Werghi, N.[Naoufel],
DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation,
CVPR25(30850-30860)
IEEE DOI 2508
Training, Image segmentation, Visualization, Uncertainty, Accuracy, Contrastive learning, Semisupervised learning, Lesions BibRef

Thakur, R.S.[Rini Smita], Kurmi, V.K.[Vinod K],
Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation,
WACV25(8035-8045)
IEEE DOI Code:
WWW Link. 2505
Training, Measurement, Couplings, Energy loss, Uncertainty, Semantic segmentation, Noise, Transformers, Data models, uncertainty, calibration BibRef

Liu, Q.Y.[Qian-Ying], Henderson, P.[Paul], Gu, X.[Xiao], Dai, H.[Hang], Deligianni, F.[Fani],
Learning Semi-Supervised Medical Image Segmentation from Spatial Registration,
WACV25(6383-6393)
IEEE DOI Code:
WWW Link. 2505
Training, Image segmentation, Computational modeling, Semantics, Transforms, Contrastive learning, Benchmark testing, Data models, transformer BibRef

Gao, N.[Ning], Zhou, S.P.[San-Ping], Wang, L.[Le], Zheng, N.N.[Nan-Ning],
PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation,
ECCV24(LXVIII: 144-160).
Springer DOI 2412
BibRef

Zhao, Z.[Zhen], Wang, Z.C.[Zi-Cheng], Wang, L.[Longyue], Yu, D.[Dian], Yuan, Y.X.[Yi-Xuan], Zhou, L.P.[Lu-Ping],
Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation,
ECCV24(V: 227-243).
Springer DOI 2412
BibRef

Miao, J.Z.[Ju-Zheng], Chen, C.[Cheng], Liu, F.[Furui], Wei, H.[Hao], Heng, P.A.[Pheng-Ann],
CauSSL: Causality-Inspired Semi-Supervised Learning for Medical Image Segmentation,
ICCV23(21369-21380)
IEEE DOI Code:
WWW Link. 2401
BibRef

Qiu, M.[Muyang], Zhang, J.[Jian], Qi, L.[Lei], Yu, Q.[Qian], Shi, Y.H.[Ying-Huan], Gao, Y.[Yang],
The Devil Is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation,
ECCV24(LIV: 74-91).
Springer DOI 2412
BibRef

Qi, W.B.[Wen-Bo], Wu, J.[Jiafei], Chan, S.C.,
Gradient-aware for Class-imbalanced Semi-supervised Medical Image Segmentation,
ECCV24(LV: 473-490).
Springer DOI 2412
BibRef

Howlader, P.[Prantik], Das, S.[Srijan], Le, H.[Hieu], Samaras, D.[Dimitris],
Beyond Pixels: Semi-supervised Semantic Segmentation with a Multi-scale Patch-based Multi-label Classifier,
ECCV24(LXXV: 342-360).
Springer DOI 2412
BibRef

Chi, H.Y.[Han-Yang], Pang, J.[Jian], Zhang, B.F.[Bing-Feng], Liu, W.F.[Wei-Feng],
Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation,
CVPR24(4070-4080)
IEEE DOI Code:
WWW Link. 2410
Image segmentation, Adaptation models, Perturbation methods, Source coding, Semantics, Predictive models, Consistency Learning BibRef

Hu, X.T.[Xin-Ting], Jiang, L.[Li], Schiele, B.[Bernt],
Training Vision Transformers for Semi-Supervised Semantic Segmentation,
CVPR24(4007-4017)
IEEE DOI Code:
WWW Link. 2410
Training, Semantic segmentation, Perturbation methods, Modulation, Transformer cores BibRef

Wang, X.Y.[Xiao-Yang], Bai, H.H.[Hui-Hui], Yu, L.M.[Li-Min], Zhao, Y.[Yao], Xiao, J.[Jimin],
Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation,
CVPR24(3303-3312)
IEEE DOI Code:
WWW Link. 2410
Training, Protocols, Perturbation methods, Semantic segmentation, Semantics, Estimation, Semisupervised learning, semi-supervised learning BibRef

Mai, H.Y.[Hua-Yu], Sun, R.[Rui], Zhang, T.Z.[Tian-Zhu], Wu, F.[Feng],
RankMatch: Exploring the Better Consistency Regularization for Semi-Supervised Semantic Segmentation,
CVPR24(3391-3401)
IEEE DOI 2410
Learning systems, Correlation, Mitochondria, Semantic segmentation, Computational modeling, Contrastive learning BibRef

Sun, B.[Boyuan], Yang, Y.Q.[Yu-Qi], Zhang, L.[Le], Cheng, M.M.[Ming-Ming], Hou, Q.[Qibin],
CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation,
CVPR24(3097-3107)
IEEE DOI Code:
WWW Link. 2410
Training, Correlation, Accuracy, Codes, Shape, Semantic segmentation, semi-supervised learning, pseudo-labeling BibRef

Wang, H.N.[Hao-Nan], Zhang, Q.X.[Qi-Xiang], Li, Y.[Yi], Li, X.M.[Xiao-Meng],
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation,
CVPR24(3627-3636)
IEEE DOI Code:
WWW Link. 2410
Training, Protocols, Semantic segmentation, Semantics, Pipelines, Manuals, Benchmark testing BibRef

Maheshwari, H.[Harsh], Liu, Y.C.[Yen-Cheng], Kira, Z.[Zsolt],
Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation,
WACV24(1009-1019)
IEEE DOI Code:
HTML Version. 2404
Training, Semantic segmentation, Benchmark testing, Robustness, Data models, Proposals, Algorithms BibRef

Liu, L.Y.[Li-Yang], Wang, Z.[Zihan], Phan, M.H.[Minh Hieu], Zhang, B.[Bowen], Ge, J.C.[Jin-Chao], Liu, Y.F.[Yi-Fan],
BPKD: Boundary Privileged Knowledge Distillation For Semantic Segmentation,
WACV24(1051-1061)
IEEE DOI Code:
WWW Link. 2404
Body regions, Adaptation models, Sensitivity, Shape, Semantic segmentation, Knowledge representation, Algorithms, Image recognition and understanding BibRef

Liu, T.[Tao], Chen, C.[Chenshu], Yang, X.[Xi], Tan, W.M.[Wen-Ming],
Rethinking Knowledge Distillation with Raw Features for Semantic Segmentation,
WACV24(1144-1153)
IEEE DOI 2404
Knowledge engineering, Sensitivity, Semantic segmentation, Feature extraction, Robustness, Tuning, Algorithms BibRef

Li, P.X.[Pei-Xia], Purkait, P.[Pulak], Ajanthan, T.[Thalaiyasingam], Abdolshah, M.[Majid], Garg, R.[Ravi], Husain, H.[Hisham], Xu, C.C.[Chen-Chen], Gould, S.[Stephen], Ouyang, W.L.[Wan-Li], van den Hengel, A.J.[Anton J.],
Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups,
ICCV23(1229-1238)
IEEE DOI 2401
BibRef

Ma, J.[Jie], Wang, C.[Chuan], Liu, Y.[Yang], Lin, L.[Liang], Li, G.B.[Guan-Bin],
Enhanced Soft Label for Semi-Supervised Semantic Segmentation,
ICCV23(1185-1195)
IEEE DOI 2401
BibRef

Dong, R.M.[Run-Min], Mou, L.C.[Li-Chao], Chen, M.X.[Meng-Xuan], Li, W.J.[Wei-Jia], Tong, X.Y.[Xin-Yi], Yuan, S.[Shuai], Zhang, L.X.[Li-Xian], Zheng, J.P.[Jue-Peng], Zhu, X.X.[Xiao Xiang], Fu, H.[Haohuan],
Large-Scale Land Cover Mapping with Fine-Grained Classes via Class-Aware Semi-Supervised Semantic Segmentation,
ICCV23(16737-16747)
IEEE DOI 2401
BibRef

Liang, C.[Chen], Wang, W.G.[Wen-Guan], Miao, J.X.[Jia-Xu], Yang, Y.[Yi],
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation,
ICCV23(16151-16162)
IEEE DOI 2401
BibRef

Zhao, Z.[Zhen], Yang, L.[Lihe], Long, S.[Sifan], Pi, J.[Jimin], Zhou, L.P.[Lu-Ping], Wang, J.D.[Jing-Dong],
Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation,
CVPR23(11350-11359)
IEEE DOI 2309
BibRef

Huang, H.M.[Hui-Min], Xie, S.[Shiao], Lin, L.F.[Lan-Fen], Tong, R.F.[Ruo-Feng], Chen, Y.W.[Yen-Wei], Li, Y.X.[Yue-Xiang], Wang, H.[Hong], Huang, Y.W.[Ya-Wen], Zheng, Y.F.[Ye-Feng],
SemiCVT: Semi-Supervised Convolutional Vision Transformer for Semantic Segmentation,
CVPR23(11340-11349)
IEEE DOI 2309
BibRef

Zhou, Y.F.[Yan-Feng], Huang, J.X.[Jia-Xing], Wang, C.L.[Chen-Long], Song, L.[Le], Yang, G.[Ge],
XNet: Wavelet-Based Low and High Frequency Fusion Networks for Fully- and Semi-Supervised Semantic Segmentation of Biomedical Images,
ICCV23(21028-21039)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wang, Z.Y.[Zi-Yang], Ma, C.Y.[Cong-Ying],
Dual-Contrastive Dual-Consistency Dual-Transformer: A Semi-Supervised Approach to Medical Image Segmentation,
NIVT23(870-879)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, Y.J.[Yi-Jiang], Wang, X.J.[Xin-Jiang], Yang, L.[Lihe], Feng, L.T.[Li-Tong], Zhang, W.[Wayne], Gao, Y.[Ying],
Diverse Cotraining Makes Strong Semi-Supervised Segmentor,
ICCV23(16009-16021)
IEEE DOI 2401
BibRef

Fang, Y.[Yan], Zhu, F.[Feng], Cheng, B.[Bowen], Liu, L.Q.[Luo-Qi], Zhao, Y.[Yao], Wei, Y.C.[Yun-Chao],
Locating Noise is Halfway Denoising for Semi-Supervised Segmentation,
ICCV23(16566-16576)
IEEE DOI 2401
BibRef

Wang, C.Q.[Chang-Qi], Xie, H.Y.[Hao-Yu], Yuan, Y.H.[Yu-Hui], Fu, C.[Chong], Yue, X.Y.[Xiang-Yu],
Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation,
ICCV23(931-942)
IEEE DOI 2401
BibRef

Kar, P.[Purbayan], Chudasama, V.[Vishal], Onoe, N.[Naoyuki], Wasnik, P.[Pankaj],
Revisiting Class Imbalance for End-to-end Semi-Supervised Object Detection,
ECV23(4570-4579)
IEEE DOI 2309
BibRef

Lao, J.W.[Jiang-Wei], Hong, W.X.[Wei-Xiang], Guo, X.[Xin], Zhang, Y.Y.[Ying-Ying], Wang, J.[Jian], Chen, J.D.[Jing-Dong], Chu, W.[Wei],
Simultaneously Short- and Long-Term Temporal Modeling for Semi-Supervised Video Semantic Segmentation,
CVPR23(14763-14772)
IEEE DOI 2309
BibRef

Wang, Z.C.[Zi-Cheng], Zhao, Z.[Zhen], Xing, X.X.[Xiao-Xia], Xu, D.[Dong], Kong, X.Y.[Xiang-Yu], Zhou, L.P.[Lu-Ping],
Conflict-Based Cross-View Consistency for Semi-Supervised Semantic Segmentation,
CVPR23(19585-19595)
IEEE DOI 2309
BibRef

Yang, L.[Lihe], Qi, L.[Lei], Feng, L.T.[Li-Tong], Zhang, W.[Wayne], Shi, Y.H.[Ying-Huan],
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation,
CVPR23(7236-7246)
IEEE DOI 2309
BibRef

Wang, X.Y.[Xiao-Yang], Zhang, B.F.[Bing-Feng], Yu, L.M.[Li-Min], Xiao, J.[Jimin],
Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic Segmentation,
CVPR23(3114-3123)
IEEE DOI 2309
BibRef

Zhang, Y.Y.[Yun-Yang], Gong, Z.Q.[Zhi-Qiang], Zhao, X.Y.[Xiao-Yu], Zheng, X.H.[Xiao-Hu], Yao, W.[Wen],
Semi-supervised Semantic Segmentation with Uncertainty-guided Self Cross Supervision,
ACCV22(VII:327-343).
Springer DOI 2307
BibRef

Rangnekar, A.[Aneesh], Kanan, C.[Christopher], Hoffman, M.[Matthew],
Semantic Segmentation with Active Semi-Supervised Learning,
WACV23(5955-5966)
IEEE DOI 2302
Training, Deep learning, Head, Costs, Annotations, Semantic segmentation, Training data, visual reasoning BibRef

Kong, H.[Heejo], Lee, G.H.[Gun-Hee], Kim, S.[Suneung], Lee, S.W.[Seong-Whan],
Pruning-Guided Curriculum Learning for Semi-Supervised Semantic Segmentation,
WACV23(5903-5912)
IEEE DOI 2302
Training, Knowledge engineering, Semantic segmentation, Benchmark testing, Feature extraction, Noise measurement BibRef

Chai, L.[Lu], Liu, Q.[Qinyuan],
Semi-Supervised Semantic Segmentation of Class-Imbalanced Images: A Hierarchical Self-Attention Generative Adversarial Network,
ICIVC22(398-404)
IEEE DOI 2301
Image segmentation, Image synthesis, Computational modeling, Biological system modeling, Semantics, Pipelines, biomedical images BibRef

Teh, E.W.[Eu Wern], de Vries, T.[Terrance], Duke, B.[Brendan], Jiang, R.[Ruowei], Aarabi, P.[Parham], Taylor, G.W.[Graham W.],
The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation,
CRV22(58-66)
IEEE DOI 2301
Greedy Iterative Self-Training (GIST) and Random Iterative Self-Training (RIST). Training, Degradation, Semantics, Semisupervised learning, Behavioral sciences, Iterative methods, Task analysis, self-training BibRef

Pauletto, L.[Loïc], Amini, M.R.[Massih-Reza], Winckler, N.[Nicolas],
Se2NAS: Self-Semi-Supervised architecture optimization for Semantic Segmentation,
ICPR22(54-60)
IEEE DOI 2212
Semantic segmentation, Training data, Artificial neural networks, Self-supervised learning, Semisupervised learning, Routing BibRef

Chen, Y.[Ying], Ouyang, X.[Xu], Zhu, K.Y.[Kai-Yue], Agam, G.[Gady],
Semi-supervised Dual-Domain Adaptation for Semantic Segmentation,
ICPR22(230-237)
IEEE DOI 2212
Deep learning, Annotations, Semantic segmentation, Supervised learning, Semisupervised learning, Benchmark testing BibRef

Qin, J.[Jie], Wu, J.[Jie], Li, M.[Ming], Xiao, X.F.[Xue-Feng], Zheng, M.[Min], Wang, X.G.[Xin-Gang],
Multi-granularity Distillation Scheme Towards Lightweight Semi-supervised Semantic Segmentation,
ECCV22(XXX:481-498).
Springer DOI 2211
BibRef

Cho, H.[Hyuna], Choi, I.[Injun], Kwak, S.[Suha], Kim, W.H.[Won Hwa],
Interactive Network Perturbation between Teacher and Students for Semi-Supervised Semantic Segmentation,
WACV24(615-624)
IEEE DOI 2404
Training, Semantic segmentation, Perturbation methods, Computational modeling, Semisupervised learning, and algorithms BibRef

Kwon, D.[Donghyeon], Kwak, S.[Suha],
Semi-supervised Semantic Segmentation with Error Localization Network,
CVPR22(9947-9957)
IEEE DOI 2210
Training, Location awareness, Degradation, Heart, Image resolution, Semisupervised learning, grouping and shape analysis BibRef

Guan, D.[Dayan], Huang, J.X.[Jia-Xing], Xiao, A.[Aoran], Lu, S.J.[Shi-Jian],
Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentation,
CVPR22(9958-9968)
IEEE DOI 2210
Deep learning, Image segmentation, Semantics, Neural networks, Object detection, Logic gates, Semisupervised learning, grouping and shape analysis BibRef

Chen, S.J.[Shuai-Jun], Jia, X.[Xu], He, J.Z.[Jian-Zhong], Shi, Y.J.[Yong-Jie], Liu, J.Z.[Jian-Zhuang],
Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation,
CVPR21(11013-11022)
IEEE DOI 2111
Training, Adaptation models, Image segmentation, Costs, Semantics, Benchmark testing BibRef

Zatsarynna, O.[Olga], Sawatzky, J.[Johann], Gall, J.[Juergen],
Discovering Latent Classes for Semi-supervised Semantic Segmentation,
GCPR20(202-217).
Springer DOI 2110
BibRef

Luo, W.F.[Wen-Feng], Yang, M.[Meng],
Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network,
ECCV20(V:784-800).
Springer DOI 2011
BibRef

Stekovic, S., Fraundorfer, F., Lepetit, V.[Vincent],
Casting Geometric Constraints in Semantic Segmentation as Semi-Supervised Learning,
WACV20(1843-1852)
IEEE DOI 2006
Image segmentation, Semantics, Predictive models, Semisupervised learning, Task analysis, Training, BibRef

Wang, Z., Wei, Y., Feris, R., Xiong, J., Hwu, W., Huang, T.S., Shi, H.,
Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation,
VL3W20(4043-4047)
IEEE DOI 2008
Semantics, Task analysis, Adaptation models, Image segmentation, Training, Feature extraction, Urban areas BibRef

Kalluri, T., Varma, G., Chandraker, M., Jawahar, C.V.,
Universal Semi-Supervised Semantic Segmentation,
ICCV19(5258-5269)
IEEE DOI 2004
entropy, image segmentation, unsupervised learning, cross-domain unsupervised losses, segmentation datasets, Roads BibRef

Wei, Y., Xiao, H., Shi, H., Jie, Z., Feng, J., Huang, T.S.,
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation,
CVPR18(7268-7277)
IEEE DOI 1812
Image segmentation, Semantics, Convolution, Training, Kernel, Standards, Head BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Efficient Semantic Segmentation, Real-Time Segmentation .