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.[Xunan],
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
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
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.[Haoyi],
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.[Yooseung],
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
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.[Jiahui],
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
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
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
Qiu, M.[Muyang],
Zhang, J.[Jian],
Qi, L.[Lei],
Yu, Q.[Qian],
Shi, Y.[Yinghuan],
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,
Computer architecture, 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
Zhou, Y.F.[Yan-Feng],
Huang, J.X.[Jia-Xing],
Wang, C.[Chenlong],
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
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
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.[Litong],
Zhang, W.[Wayne],
Shi, Y.[Yinghuan],
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
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
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
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 .