8.6.3.6 Weakly Supervised, Self Supervised Semantic Segmentation

Chapter Contents (Back)
Semantic Segmentation. Weakly Supervised. Self-Supervised.

Li, Y.[Yi], Guo, Y.Q.[Yan-Qing], Kao, Y.Y.[Yue-Ying], He, R.[Ran],
Image Piece Learning for Weakly Supervised Semantic Segmentation,
SMCS(47), No. 4, April 2017, pp. 648-659.
IEEE DOI 1704
Correlation BibRef

Shimoda, W.[Wataru], Yanai, K.[Keiji],
Weakly supervised semantic segmentation using distinct class specific saliency maps,
CVIU(191), 2020, pp. 102712.
Elsevier DOI 2002
BibRef
Earlier:
Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation,
ECCV16(IV: 218-234).
Springer DOI 1611
Semantic segmentation, Weakly supervised learning, Weakly supervised segmentation, Visualization, Deep learning BibRef

Shimoda, W.[Wataru], Yanai, K.[Keiji],
Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation,
ICCV19(5207-5216)
IEEE DOI 2004
estimation theory, image denoising, image segmentation, iterative methods, learning (artificial intelligence), Predictive models BibRef

Chen, Y.C.[Yun-Chun], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan], Huang, J.B.[Jia-Bin],
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-Segmentation,
PAMI(43), No. 10, October 2021, pp. 3632-3647.
IEEE DOI 2109
Semantics, Task analysis, Image segmentation, Training, Clutter, Proposals, Pattern matching, Semantic matching, weakly-supervised learning BibRef

Zhou, T.F.[Tian-Fei], Li, L.L.[Liu-Lei], Li, X.Y.[Xue-Yi], Feng, C.M.[Chun-Mei], Li, J.W.[Jian-Wu], Shao, L.[Ling],
Group-Wise Learning for Weakly Supervised Semantic Segmentation,
IP(31), 2022, pp. 799-811.
IEEE DOI 2201
Semantics, Image segmentation, Training, Location awareness, Cognition, Task analysis, Graph neural networks, neural attention BibRef

Zhou, T.F.[Tian-Fei], Zhang, M.J.[Mei-Jie], Zhao, F.[Fang], Li, J.W.[Jian-Wu],
Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic Segmentation,
CVPR22(4289-4299)
IEEE DOI 2210
Training, Location awareness, Annotations, Semantics, Training data, Benchmark testing, Segmentation, grouping and shape analysis, Scene analysis and understanding BibRef

Chen, H.J.[Hong-Jun], Wang, J.B.[Jin-Bao], Chen, H.C.[Hong Cai], Zhen, X.T.[Xian-Tong], Zheng, F.[Feng], Ji, R.R.[Rong-Rong], Shao, L.[Ling],
Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation,
ICCV21(6900-6909)
IEEE DOI 2203
Seminars, Training, Knowledge engineering, Bridges, Costs, Annotations, Segmentation, grouping and shape, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zhang, R.M.[Rui-Mao], Lin, L.[Liang], Wang, G.R.[Guang-Run], Wang, M.[Meng], Zuo, W.M.[Wang-Meng],
Hierarchical Scene Parsing by Weakly Supervised Learning with Image Descriptions,
PAMI(41), No. 3, March 2019, pp. 596-610.
IEEE DOI 1902
Semantics, Labeling, Training, Neural networks, Task analysis, Predictive models, Image segmentation, Scene parsing, recursive structured prediction BibRef

Qu, M.X.[Meng-Xue], Wu, Y.[Yu], Wei, Y.C.[Yun-Chao], Liu, W.[Wu], Liang, X.D.[Xiao-Dan], Zhao, Y.[Yao],
Learning to Segment Every Referring Object Point by Point,
CVPR23(3021-3030)
IEEE DOI 2309
BibRef

Lin, L.[Liang], Wang, G.R.[Guang-Run], Zhang, R.[Rui], Zhang, R.M.[Rui-Mao], Liang, X.D.[Xiao-Dan], Zuo, W.M.[Wang-Meng],
Deep Structured Scene Parsing by Learning with Image Descriptions,
CVPR16(2276-2284)
IEEE DOI 1612
BibRef

Wang, X.A.[Xi-Ang], Liu, S.F.[Si-Fei], Ma, H.M.[Hui-Min], Yang, M.H.[Ming-Hsuan],
Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning,
IJCV(128), No. 6, June 2020, pp. 1736-1749.
Springer DOI 2006
BibRef

Chan, L.[Lyndon], Hosseini, M.S.[Mahdi S.], Plataniotis, K.N.[Konstantinos N.],
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains,
IJCV(129), No. 2, February 2021, pp. 361-384.
Springer DOI 2102
BibRef

Krešo, I.[Ivan], Krapac, J.[Josip], Šegvic, S.[Siniša],
Efficient Ladder-Style DenseNets for Semantic Segmentation of Large Images,
ITS(22), No. 8, August 2021, pp. 4951-4961.
IEEE DOI 2108
BibRef
Earlier: A2, A1, A3:
Ladder-Style DenseNets for Semantic Segmentation of Large Natural Images,
CVRoads17(238-245)
IEEE DOI 1802
BibRef
Earlier: A2, A3, Only:
Weakly-Supervised Semantic Segmentation by Redistributing Region Scores Back to the Pixels,
GCPR16(377-388).
Springer DOI 1611
Semantics, Feature extraction, Image segmentation, Computational modeling, Spatial resolution, Checkpointing, road transportation. Convolution, Tensile stress, Training BibRef

Krešo, I.[Ivan], Cauševic, D.[Denis], Krapac, J.[Josip], Šegvic, S.[Siniša],
Convolutional Scale Invariance for Semantic Segmentation,
GCPR16(64-75).
Springer DOI 1611
BibRef

Zhang, B.F.[Bing-Feng], Xiao, J.[Jimin], Wei, Y.C.[Yun-Chao], Huang, K.[Kaizhu], Luo, S.[Shan], Zhao, Y.[Yao],
End-to-end weakly supervised semantic segmentation with reliable region mining,
PR(128), 2022, pp. 108663.
Elsevier DOI 2205
Weakly supervised, Semantic segmentation, End-to-end, Attention BibRef

Jiang, P.T.[Peng-Tao], Han, L.H.[Ling-Hao], Hou, Q.B.[Qi-Bin], Cheng, M.M.[Ming-Ming], Wei, Y.C.[Yun-Chao],
Online Attention Accumulation for Weakly Supervised Semantic Segmentation,
PAMI(44), No. 10, October 2022, pp. 7062-7077.
IEEE DOI 2209
Training, Semantics, Cats, Image segmentation, Visualization, Task analysis, Location awareness, pixel-level supervision BibRef

Zhang, B.F.[Bing-Feng], Xiao, J.[Jimin], Jiao, J.B.[Jian-Bo], Wei, Y.C.[Yun-Chao], Zhao, Y.[Yao],
Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation,
PAMI(44), No. 11, November 2022, pp. 8082-8096.
IEEE DOI 2210
Semantics, Task analysis, Image edge detection, Image segmentation, Reliability, Proposals, Graph neural networks, Weakly supervised, graph neural network BibRef

Zhang, B.F.[Bing-Feng], Xiao, J.M.[Ji-Min], Wei, Y.C.[Yun-Chao], Zhao, Y.[Yao],
Credible Dual-Expert Learning for Weakly Supervised Semantic Segmentation,
IJCV(131), No. 8, August 2023, pp. 1892-1908.
Springer DOI 2307
BibRef

Xia, R.Y.[Rui-Yang], Li, G.Q.[Guo-Quan], Huang, Z.W.[Zheng-Wen], Meng, H.Y.[Hong-Ying], Pang, Y.[Yu],
CBASH: Combined Backbone and Advanced Selection Heads With Object Semantic Proposals for Weakly Supervised Object Detection,
CirSysVideo(32), No. 10, October 2022, pp. 6502-6514.
IEEE DOI 2210
Proposals, Semantics, Feature extraction, Object detection, Training, Location awareness, Head, Weakly supervised object detection, object semantic proposals BibRef

Zhou, H.J.[Hua-Jun], Yang, L.X.[Ling-Xiao], Xie, X.H.[Xiao-Hua], Lai, J.H.[Jian-Huang],
Selective Intra-Image Similarity for Personalized Fixation-Based Object Segmentation,
CirSysVideo(32), No. 11, November 2022, pp. 7910-7923.
IEEE DOI 2211
Image segmentation, Task analysis, Object segmentation, Observers, Image edge detection, Object detection, Measurement, evaluation metric BibRef

Chen, Q.[Qi], Yang, L.X.[Ling-Xiao], Lai, J.H.[Jian-Huang], Xie, X.H.[Xiao-Hua],
Self-supervised Image-specific Prototype Exploration for Weakly Supervised Semantic Segmentation,
CVPR22(4278-4288)
IEEE DOI 2210
Location awareness, Weight measurement, Image segmentation, Costs, Shape, Semantics, Prototypes, Segmentation, Self- semi- meta- unsupervised learning BibRef

Fasana, C.[Corrado], Pasini, S.[Samuele], Milani, F.[Federico], Fraternali, P.[Piero],
Weakly Supervised Object Detection for Remote Sensing Images: A Survey,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, Y.J.[Yu-Jie], Sun, J.X.[Jia-Xing], Li, Y.[Yun],
Weakly-Supervised Semantic Segmentation Network With Iterative dCRF,
ITS(23), No. 12, December 2022, pp. 25419-25426.
IEEE DOI 2212
Semantics, Cams, Image segmentation, Convolution, Annotations, Feature extraction, Training, Weakly-supervised, image-level annotations BibRef

Cheng, L.[Lin], Fang, P.F.[Peng-Fei], Yan, Y.[Yan], Lu, Y.[Yang], Wang, H.Z.[Han-Zi],
TRL: Transformer based refinement learning for hybrid-supervised semantic segmentation,
PRL(164), 2022, pp. 239-245.
Elsevier DOI 2212
Hybrid-supervised semantic segmentation, Simi-supervised semantic segmentation, Pseudo label BibRef

Feng, J.[Jiapei], Wang, X.G.[Xing-Gang], Li, T.[Te], Ji, S.S.[Shan-Shan], Liu, W.Y.[Wen-Yu],
Weakly-supervised semantic segmentation via online pseudo-mask correcting,
PRL(165), 2023, pp. 33-38.
Elsevier DOI 2301
Weakly-supervised learning, Semantic segmentation, Noisy label learning BibRef

Min, H.[Hai], Zhang, Y.[Yemao], Zhao, Y.[Yang], Jia, W.[Wei], Lei, Y.K.[Ying-Ke], Fan, C.X.[Chun-Xiao],
Hybrid feature enhancement network for few-shot semantic segmentation,
PR(137), 2023, pp. 109291.
Elsevier DOI 2302
Semantic segmentation, Few-shot segmentation, Few-shot learning BibRef

Yuan, K.H.[Kun-Hao], Schaefer, G.[Gerald], Lai, Y.K.[Yu-Kun], Wang, Y.F.[Yi-Fan], Liu, X.[Xiyao], Guan, L.[Lin], Fang, H.[Hui],
A multi-strategy contrastive learning framework for weakly supervised semantic segmentation,
PR(137), 2023, pp. 109298.
Elsevier DOI 2302
Weakly supervised learning, Representation learning, Contrastive learning, Semantic segmentation BibRef

Li, R.[Ruiwen], Mai, Z.[Zheda], Zhang, Z.B.[Zhi-Bo], Jang, J.[Jongseong], Sanner, S.[Scott],
TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation,
JVCIR(92), 2023, pp. 103800.
Elsevier DOI 2303
Weakly supervised learning, Semantic segmentation, Vision transformer BibRef

Fan, J.S.[Jun-Song], Zhang, Z.X.[Zhao-Xiang],
Memory-Based Cross-Image Contexts for Weakly Supervised Semantic Segmentation,
PAMI(45), No. 5, May 2023, pp. 6006-6020.
IEEE DOI 2304
Image segmentation, Semantics, Training, Heating systems, Context modeling, Task analysis, Computational modeling, cross-image context BibRef

Liu, W.[Weide], Kong, X.F.[Xiang-Fei], Hung, T.Y.[Tzu-Yi], Lin, G.S.[Guo-Sheng],
Cross-Image Region Mining With Region Prototypical Network for Weakly Supervised Segmentation,
MultMed(25), 2023, pp. 1148-1160.
IEEE DOI 2305
Prototypes, Training, Semantics, Image segmentation, Task analysis, Robustness, Annotations, Cross-image, weakly-supervised, segmentation BibRef

Chen, T.[Tao], Yao, Y.Z.[Ya-Zhou], Tang, J.H.[Jin-Hui],
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic Segmentation,
IP(32), 2023, pp. 2960-2971.
IEEE DOI 2306
Training, Noise measurement, Task analysis, Cams, Semantic segmentation, Filtering, Adversarial machine learning, noisy label BibRef

Li, J.L.[Jin-Long], Jie, Z.[Zequn], Wang, X.[Xu], Zhou, Y.[Yu], Wei, X.L.[Xiao-Lin], Ma, L.[Lin],
Weakly Supervised Semantic Segmentation via Progressive Patch Learning,
MultMed(25), 2023, pp. 1686-1699.
IEEE DOI 2306
Training, Semantics, Image segmentation, Task analysis, Sensitivity, Location awareness, Annotations, Weakly supervised learning, progressive learning BibRef

Chen, T.[Tao], Yao, Y.Z.[Ya-Zhou], Zhang, L.[Lei], Wang, Q.[Qiong], Xie, G.S.[Guo-Sen], Shen, F.M.[Fu-Min],
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic Segmentation,
MultMed(25), 2023, pp. 1727-1737.
IEEE DOI 2306
Cams, Image segmentation, Semantics, Task analysis, Training, Prototypes, Location awareness, Semantic segmentation, relation constraint BibRef

Chen, T.[Tao], Yao, Y.Z.[Ya-Zhou], Huang, X.[Xingguo], Li, Z.C.[Ze-Chao], Nie, L.Q.[Li-Qiang], Tang, J.H.[Jin-Hui],
Spatial Structure Constraints for Weakly Supervised Semantic Segmentation,
IP(33), 2024, pp. 1136-1148.
IEEE DOI Code:
WWW Link. 2402
Cams, Semantic segmentation, Image reconstruction, Training, Task analysis, Annotations, Semantics, Semantic segmentation, spatial structure constraints BibRef

Lei, J.[Jie], Yang, G.Y.[Guo-Yu], Wang, S.W.[Shuai-Wei], Feng, Z.L.[Zun-Lei], Liang, R.H.[Rong-Hua],
DCAM: Disturbed class activation maps for weakly supervised semantic segmentation,
JVCIR(94), 2023, pp. 103852.
Elsevier DOI 2306
Weakly supervised semantic segmentation, Class activation map, Image-level class label, Disturbance injection BibRef

Zhu, M.[Meilu], Chen, Z.[Zhen], Yuan, Y.X.[Yi-Xuan],
FedDM: Federated Weakly Supervised Segmentation via Annotation Calibration and Gradient De-Conflicting,
MedImg(42), No. 6, June 2023, pp. 1632-1643.
IEEE DOI 2306
Annotations, Training, Noise measurement, Data models, Image segmentation, Servers, Adaptation models, Federated learning, medical image segmentation BibRef

Yin, Y.F.[Yu-Fei], Deng, J.J.[Jia-Jun], Zhou, W.G.[Wen-Gang], Li, L.[Li], Li, H.Q.[Hou-Qiang],
FI-WSOD: Foreground Information Guided Weakly Supervised Object Detection,
MultMed(25), 2023, pp. 1890-1902.
IEEE DOI 2306
Task analysis, Proposals, Detectors, Object detection, Training, Feature extraction, Noise measurement, Object detection, weakly supervised learning BibRef

Gama, P.H.T.[Pedro H. T.], Oliveira, H.[Hugo], Marcato-Junior, J.[José], dos Santos, J.A.[Jefersson A.],
Weakly Supervised Few-Shot Segmentation via Meta-Learning,
MultMed(25), 2023, pp. 1784-1797.
IEEE DOI 2306
Image segmentation, Task analysis, Semantics, Annotations, Prototypes, Biomedical imaging, Training, Agriculture, few-shot, weakly supervised BibRef

Pu, Y.N.[Yan-Nan], Sun, J.[Jian], Tang, N.S.[Nian-Sheng], Xu, Z.B.[Zong-Ben],
Deep expectation-maximization network for unsupervised image segmentation and clustering,
IVC(135), 2023, pp. 104717.
Elsevier DOI 2306
Deep clustering, EM algorithm, Image clustering, Representation learning, Unsupervised image segmentation BibRef

Shen, W.[Wei], Peng, Z.L.[Ze-Lin], Wang, X.[Xuehui], Wang, H.Y.[Hua-Yu], Cen, J.Z.[Jia-Zhong], Jiang, D.S.[Dong-Sheng], Xie, L.X.[Ling-Xi], Yang, X.K.[Xiao-Kang], Tian, Q.[Qi],
A Survey on Label-Efficient Deep Image Segmentation: Bridging the Gap Between Weak Supervision and Dense Prediction,
PAMI(45), No. 8, August 2023, pp. 9284-9305.
IEEE DOI 2307
Semantic segmentation, Semantics, Training, Annotations, Task analysis, Taxonomy, Sports equipment, Instance segmentation, weakly-supervised learning BibRef

Zhu, Y.[Yueyi], Zhang, Y.Q.[Yong-Qiang], Ding, M.L.[Ming-Li], Zuo, W.M.[Wang-Meng],
Uncertainty-Aware Graph-Guided Weakly Supervised Object Detection,
CirSysVideo(33), No. 7, July 2023, pp. 3257-3269.
IEEE DOI 2307
Task analysis, Proposals, Uncertainty, Object detection, Location awareness, Training, Annotations, graph convolution network BibRef

Li, Y.Q.[Yu-Qiang], Wu, Y.[Ying], Liu, C.[Chun], Wu, X.[Xinyi],
IAC-ReCAM: Two-dimensional attention modulation and category label guidance for weakly supervised semantic segmentation,
IVC(136), 2023, pp. 104738.
Elsevier DOI 2308
Semantic segmentation, Weakly supervised learning, Attention modulation BibRef

Chen, J.L.[Jun-Liang], Lu, W.Z.[Wei-Zeng], Li, Y.X.[Yue-Xiang], Shen, L.L.[Lin-Lin], Duan, J.M.[Jin-Ming],
Adversarial Learning of Object-Aware Activation Map for Weakly-Supervised Semantic Segmentation,
CirSysVideo(33), No. 8, August 2023, pp. 3935-3946.
IEEE DOI 2308
Cams, Semantic segmentation, Training, Task analysis, Streaming media, Semantics, Object segmentation, object-aware activation map BibRef

Huang, Z.[Zuxian], Wu, G.S.[Gang-Shan], Wang, L.M.[Li-Min],
Webly-supervised semantic segmentation via curriculum learning,
CVIU(236), 2023, pp. 103810.
Elsevier DOI 2310
Image Segmentation, Webly supervised learning, Weakly supervised learning BibRef

Song, C.F.[Chun-Feng], Ouyang, W.L.[Wan-Li], Zhang, Z.X.[Zhao-Xiang],
Weakly Supervised Semantic Segmentation via Box-Driven Masking and Filling Rate Shifting,
PAMI(45), No. 12, December 2023, pp. 15996-16012.
IEEE DOI 2311
BibRef

Song, C.F.[Chun-Feng], Huang, Y.[Yan], Ouyang, W.L.[Wan-Li], Wang, L.[Liang],
Box-Driven Class-Wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation,
CVPR19(3131-3140).
IEEE DOI 2002
BibRef

Xu, L.[Lian], Ouyang, W.L.[Wan-Li], Bennamoun, M.[Mohammed], Boussaid, F.[Farid], Xu, D.[Dan],
Learning Multi-Modal Class-Specific Tokens for Weakly Supervised Dense Object Localization,
CVPR23(19596-19605)
IEEE DOI 2309
BibRef
Earlier:
Multi-class Token Transformer for Weakly Supervised Semantic Segmentation,
CVPR22(4300-4309)
IEEE DOI 2210
Location awareness, Shape, Semantics, Object detection, Transformers, Pattern recognition, Segmentation, grouping and shape analysis BibRef

Fan, J.S.[Jun-Song], Zhang, Z.X.[Zhao-Xiang],
Toward Practical Weakly Supervised Semantic Segmentation via Point-Level Supervision,
IJCV(131), No. 12, December 2023, pp. 3252-3271.
Springer DOI 2311
BibRef

Chen, M.[Man], Xu, K.[Kun], Chen, E.[Enping], Zhang, Y.[Yao], Xie, Y.F.[Yi-Fei], Hu, Y.[Yahao], Pan, Z.S.[Zhi-Song],
Semantic Attention and Structured Model for Weakly Supervised Instance Segmentation in Optical and SAR Remote Sensing Imagery,
RS(15), No. 21, 2023, pp. 5201.
DOI Link 2311
BibRef

Zhang, M.[Man], Zhou, Y.[Yong], Liu, B.[Bing], Zhao, J.Q.[Jia-Qi], Yao, R.[Rui], Shao, Z.W.[Zhi-Wen], Zhu, H.C.[Han-Cheng],
Weakly Supervised Few-Shot Semantic Segmentation via Pseudo Mask Enhancement and Meta Learning,
MultMed(25), 2023, pp. 7980-7991.
IEEE DOI 2312
BibRef

Zhang, Y.H.[Yu-Hang], Tian, S.[Shishun], Liao, M.[Muxin], Zhang, Z.Y.[Zheng-Yu], Zou, W.B.[Wen-Bin], Xu, C.[Chen],
Fine-Grained Self-Supervision for Generalizable Semantic Segmentation,
CirSysVideo(34), No. 1, January 2024, pp. 371-383.
IEEE DOI 2401
BibRef

Yaganapu, A.[Avinash], Kang, M.[Mingon],
Multi-layered self-attention mechanism for weakly supervised semantic segmentation,
CVIU(239), 2024, pp. 103886.
Elsevier DOI 2402
Weakly supervised semantic segmentation, Segmentation, Self-attention, Image-level labels BibRef

Wang, W.G.[Wen-Guan], Sun, G.L.[Guo-Lei], Van Gool, L.J.[Luc J.],
Looking Beyond Single Images for Weakly Supervised Semantic Segmentation Learning,
PAMI(46), No. 3, March 2024, pp. 1635-1649.
IEEE DOI 2402
Semantics, Image segmentation, Location awareness, Training, Birds, Training data, Noise measurement, Semantic segmentation, cross-image semantic relation BibRef

Sun, G.L.[Guo-Lei], Wang, W.G.[Wen-Guan], Dai, J.F.[Ji-Feng], Van Gool, L.J.[Luc J.],
Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation,
ECCV20(II:347-365).
Springer DOI 2011
BibRef

Xu, R.T.[Rong-Tao], Wang, C.W.[Chang-Wei], Xu, S.B.[Shi-Biao], Meng, W.L.[Wei-Liang], Zhang, X.P.[Xiao-Peng],
Wave-Like Class Activation Map With Representation Fusion for Weakly-Supervised Semantic Segmentation,
MultMed(26), 2024, pp. 581-592.
IEEE DOI 2402
Semantics, Semantic segmentation, Adaptation models, Wave functions, Training, Task analysis, Fuses, Class activation map, weakly supervised semantic segmentation BibRef

Li, J.X.[Jun-Xia], Shi, D.[Deshuo], Cui, Y.[Ying], Guo, D.Y.[Dong-Yan], Liu, Q.S.[Qing-Shan],
Adaptive Activation Network for Weakly Supervised Semantic Segmentation,
MultMed(26), 2024, pp. 6078-6089.
IEEE DOI 2404
Semantic segmentation, Task analysis, Semantics, Adaptive systems, Training, Noise reduction, Annotations, scale adaptation BibRef

Zheng, S.D.[Shang-Dong], Wu, Z.B.[Ze-Bin], Xu, Y.[Yang], Wei, Z.H.[Zhi-Hui],
Weakly Supervised Object Detection for Remote Sensing Images via Progressive Image-Level and Instance-Level Feature Refinement,
RS(16), No. 7, 2024, pp. 1203.
DOI Link 2404
BibRef

Kim, H.[Hyoseo], Choe, J.[Junsuk],
Weakly-Supervised Incremental Learning for Semantic Segmentation with Class Hierarchy,
PRL(182), 2024, pp. 31-38.
Elsevier DOI 2405
Machine learning, Deep learning, Semantic segmentation, Weak supervision, Incremental learning BibRef

Qian, X.L.[Xiao-Liang], Lin, C.Y.[Chen-Yang], Chen, Z.W.[Zhi-Wu], Wang, W.[Wei],
SAM-Induced Pseudo Fully Supervised Learning for Weakly Supervised Object Detection in Remote Sensing Images,
RS(16), No. 9, 2024, pp. 1532.
DOI Link 2405
BibRef


Tay, C.P.[Chiat-Pin], Subbaraju, V.[Vigneshwaran], Kandappu, T.[Thivya],
PrivObfNet: A Weakly Supervised Semantic Segmentation Model for Data Protection,
WACV24(2410-2420)
IEEE DOI 2404
Privacy, Correlation, Social networking (online), Semantic segmentation, Computational modeling, Urban areas, Vision + language and/or other modalities BibRef

Jonnarth, A.[Arvi], Zhang, Y.S.[Yu-Shan], Felsberg, M.[Michael],
High-fidelity Pseudo-labels for Boosting Weakly-Supervised Segmentation,
WACV24(999-1008)
IEEE DOI Code:
WWW Link. 2404
Training, Image segmentation, Monte Carlo methods, Image color analysis, Semantic segmentation BibRef

Kwon, J.[JuneHyoung], Lee, E.[Eunju], Cho, Y.[Yunsung], Kim, Y.[YoungBin],
Learning to Detour: Shortcut Mitigating Augmentation for Weakly Supervised Semantic Segmentation,
WACV24(808-817)
IEEE DOI 2404
Location awareness, Training, Measurement, Costs, Correlation, Semantic segmentation, Algorithms BibRef

Yang, X.B.[Xiao-Bo], Gong, X.J.[Xiao-Jin],
Foundation Model Assisted Weakly Supervised Semantic Segmentation,
WACV24(512-521)
IEEE DOI 2404
Training, Codes, Semantic segmentation, Task analysis, Image classification, Algorithms, Vision + language and/or other modalities BibRef

Mun, C.[Cheolhyun], Lee, S.[Sanghuk], Uh, Y.J.[Young-Jung], Choe, J.[Junsuk], Byun, H.R.[Hye-Ran],
Small Objects Matters in Weakly-supervised Semantic Segmentation,
WACV24(413-422)
IEEE DOI 2404
Training, Measurement, Semantic segmentation, Task analysis, Algorithms, Image recognition and understanding, Algorithms, Datasets and evaluations BibRef

Murugesan, B.[Balamurali], Hussain, R.[Rukhshanda], Bhattacharya, R.[Rajarshi], Ben Ayed, I.[Ismail], Dolz, J.[Jose],
Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation,
WACV24(290-301)
IEEE DOI 2404
Adaptation models, Codes, Semantic segmentation, Focusing, Benchmark testing, Performance gain, Algorithms, Vision + language and/or other modalities BibRef

Wu, F.W.[Fang-Wen], He, J.X.[Jing-Xuan], Yin, Y.F.[Yu-Fei], Hao, Y.B.[Yan-Bin], Huang, G.[Gang], Cheng, L.[Lechao],
Masked Collaborative Contrast for Weakly Supervised Semantic Segmentation,
WACV24(851-860)
IEEE DOI Code:
WWW Link. 2404
Semantic segmentation, Source coding, Computational modeling, Semantics, Collaboration, Self-supervised learning, Algorithms BibRef

Yin, Y.F.[Yu-Fei], Deng, J.J.[Jia-Jun], Zhou, W.G.[Wen-Gang], Li, L.[Li], Li, H.Q.[Hou-Qiang],
Cyclic-Bootstrap Labeling for Weakly Supervised Object Detection,
ICCV23(6985-6995)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, L.[Liyi], Lei, C.Y.[Chen-Yang], Li, R.H.[Rui-Huang], Li, S.[Shuai], Zhang, Z.X.[Zhao-Xiang], Zhang, L.[Lei],
FPR: False Positive Rectification for Weakly Supervised Semantic Segmentation,
ICCV23(1108-1118)
IEEE DOI Code:
WWW Link. 2401
BibRef

Shinoda, R.[Risa], Hayamizu, R.[Ryo], Nakashima, K.[Kodai], Inoue, N.[Nakamasa], Yokota, R.[Rio], Kataoka, H.[Hirokatsu],
SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning,
ICCV23(19997-20006)
IEEE DOI Code:
WWW Link. 2401
BibRef

Peng, Z.L.[Ze-Lin], Wang, G.[Guanchun], Xie, L.X.[Ling-Xi], Jiang, D.S.[Dong-Sheng], Shen, W.[Wei], Tian, Q.[Qi],
USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation,
ICCV23(624-634)
IEEE DOI 2401
BibRef

Karimijafarbigloo, S.[Sanaz], Azad, R.[Reza], Kazerouni, A.[Amirhossein], Velichko, Y.[Yury], Bagci, U.[Ulas], Merhof, D.[Dorit],
Self-supervised Semantic Segmentation: Consistency over Transformation,
CVAMD23(2646-2655)
IEEE DOI 2401
BibRef

Wang, C.W.[Chang-Wei], Xu, R.T.[Rong-Tao], Xu, S.B.[Shi-Biao], Meng, W.L.[Wei-Liang], Zhang, X.P.[Xiao-Peng],
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation,
ICCV23(755-765)
IEEE DOI 2401
BibRef

Jo, S.[Sanghyun], Yu, I.J.[In-Jae], Kim, K.[Kyungsu],
MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation,
ICCV23(614-623)
IEEE DOI Code:
WWW Link. 2401
BibRef

Deng, Z.J.[Zhi-Jie], Luo, Y.[Yucen],
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation,
ICCV23(551-561)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sun, W.X.[Wei-Xuan], Zhang, Y.H.[Yan-Hao], Qin, Z.[Zhen], Liu, Z.Y.[Zhe-Yuan], Cheng, L.[Lin], Wang, F.[Fanyi], Zhong, Y.[Yiran], Barnes, N.M.[Nick M.],
All-Pairs Consistency Learning for Weakly Supervised Semantic Segmentation,
NIVT23(826-837)
IEEE DOI 2401
BibRef

Liu, Y.[Yanan], Zhang, L.[Libao],
Mutually Supervised Learning via Interactive Consistency for Geographic Object Segmentation from Weakly Labeled Remote Sensing Imagery,
ICIP23(2985-2989)
IEEE DOI 2312
BibRef

Zhang, H.[Hao], Li, F.[Feng], Xu, H.Z.[Huai-Zhe], Huang, S.J.[Shi-Jia], Liu, S.L.[Shi-Long], Ni, L.M.[Lionel M.], Zhang, L.[Lei],
MP-Former: Mask-Piloted Transformer for Image Segmentation,
CVPR23(18074-18083)
IEEE DOI 2309
BibRef

Reiß, S.[Simon], Seibold, C.[Constantin], Freytag, A.[Alexander], Rodner, E.[Erik], Stiefelhagen, R.[Rainer],
Decoupled Semantic Prototypes enable learning from diverse annotation types for semi-weakly segmentation in expert-driven domains,
CVPR23(15495-15506)
IEEE DOI 2309
BibRef

Chen, Z.Z.[Zhao-Zheng], Sun, Q.R.[Qian-Ru],
Extracting Class Activation Maps from Non-Discriminative Features as well,
CVPR23(3135-3144)
IEEE DOI 2309

WWW Link. BibRef

Wu, L.S.[Lin-Shan], Zhong, Z.[Zhun], Fang, L.Y.[Le-Yuan], He, X.X.[Xing-Xin], Liu, Q.[Qiang], Ma, J.Y.[Jia-Yi], Chen, H.[Hao],
Sparsely Annotated Semantic Segmentation with Adaptive Gaussian Mixtures,
CVPR23(15454-15464)
IEEE DOI 2309
BibRef

Feng, Q.L.[Qian-Li], Gadde, R.[Raghudeep], Liao, W.[Wentong], Ramon, E.[Eduard], Martinez, A.[Aleix],
Network-Free, Unsupervised Semantic Segmentation with Synthetic Images,
CVPR23(23602-23610)
IEEE DOI 2309
BibRef

Yu, C.[Chaohui], Zhou, Q.[Qiang], Li, J.L.[Jing-Liang], Yuan, J.L.[Jian-Long], Wang, Z.B.[Zhi-Bin], Wang, F.[Fan],
Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation,
CVPR23(23685-23694)
IEEE DOI 2309
BibRef

Cheng, Z.[Zesen], Qiao, P.C.[Peng-Chong], Li, K.[Kehan], Li, S.H.[Si-Heng], Wei, P.X.[Peng-Xu], Ji, X.Y.[Xiang-Yang], Yuan, L.[Li], Liu, C.[Chang], Chen, J.[Jie],
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation,
CVPR23(23673-23684)
IEEE DOI 2309
BibRef

Hanna, J.[Joëlle], Mommert, M.[Michael], Borth, D.[Damian],
Sparse Multimodal Vision Transformer for Weakly Supervised Semantic Segmentation,
EarthVision23(2145-2154)
IEEE DOI 2309
BibRef

Cheng, T.H.[Tian-Heng], Wang, X.G.[Xing-Gang], Chen, S.Y.[Shao-Yu], Zhang, Q.[Qian], Liu, W.Y.[Wen-Yu],
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation,
CVPR23(3145-3154)
IEEE DOI 2309
BibRef

Kim, B.[Beomyoung], Jeong, J.[Joonhyun], Han, D.Y.[Dong-Yoon], Hwang, S.J.[Sung Ju],
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation,
CVPR23(11360-11370)
IEEE DOI 2309
BibRef

Wang, Y.C.[Yu-Chao], Fei, J.J.[Jing-Jing], Wang, H.C.[Hao-Chen], Li, W.[Wei], Bao, T.P.[Tian-Peng], Wu, L.W.[Li-Wei], Zhao, R.[Rui], Shen, Y.J.[Yu-Jun],
Balancing Logit Variation for Long-Tailed Semantic Segmentation,
CVPR23(19561-19573)
IEEE DOI 2309
BibRef

Zhong, Z.S.[Zhi-Sheng], Cui, J.[Jiequan], Yang, Y.[Yibo], Wu, X.Y.[Xiao-Yang], Qi, X.J.[Xiao-Juan], Zhang, X.Y.[Xiang-Yu], Jia, J.Y.[Jia-Ya],
Understanding Imbalanced Semantic Segmentation Through Neural Collapse,
CVPR23(19550-19559)
IEEE DOI 2309
BibRef

Seong, H.S.[Hyun Seok], Moon, W.[WonJun], Lee, S.[SuBeen], Heo, J.P.[Jae-Pil],
Leveraging Hidden Positives for Unsupervised Semantic Segmentation,
CVPR23(19540-19549)
IEEE DOI 2309
BibRef

Li, K.[Kehan], Wang, Z.[Zhennan], Cheng, Z.[Zesen], Yu, R.[Runyi], Zhao, Y.F.[Yi-Fan], Song, G.[Guoli], Liu, C.[Chang], Yuan, L.[Li], Chen, J.[Jie],
ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation,
CVPR23(7162-7172)
IEEE DOI 2309
BibRef

Yang, Y.[Yong], Chen, Q.[Qiong], Feng, Y.[Yuan], Huang, T.[Tianlin],
MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation,
CVPR23(7131-7140)
IEEE DOI 2309
BibRef

Ru, L.X.[Li-Xiang], Zheng, H.L.[He-Liang], Zhan, Y.B.[Yi-Bing], Du, B.[Bo],
Token Contrast for Weakly-Supervised Semantic Segmentation,
CVPR23(3093-3102)
IEEE DOI 2309
BibRef

Zhang, H.R.[Hong-Run], Burrows, L.[Liam], Meng, Y.[Yanda], Sculthorpe, D.[Declan], Mukherjee, A.[Abhik], Coupland, S.E.[Sarah E], Chen, K.[Ke], Zheng, Y.L.[Ya-Lin],
Weakly Supervised Segmentation with Point Annotations for Histopathology Images via Contrast-Based Variational Model,
CVPR23(15630-15640)
IEEE DOI 2309
BibRef

Akiva, P.[Peri], Dana, K.[Kristin],
Single Stage Weakly Supervised Semantic Segmentation of Complex Scenes,
WACV23(5943-5954)
IEEE DOI 2302
Training, Annotations, Semantic segmentation, Semantics, Focusing, Benchmark testing, Applications: Agriculture, Remote Sensing BibRef

Cheng, W.L.[Wen-Li], Jiao, J.J.[Jia-Jia],
CAU: A Consensus Model of Augmented Unlabeled Data for Medical Image Segmentation,
ICIVC22(368-374)
IEEE DOI 2301
Training, Image segmentation, Machine learning algorithms, Semisupervised learning, Prediction algorithms, Data models, Data Augmentation BibRef

Fan, Z.K.[Zhen-Kun], Sun, X.[Xin], Dong, J.Y.[Jun-Yu],
Average Activation Network for Weakly Supervised Semantic Segmentation,
ICPR22(657-662)
IEEE DOI 2212
Training, Limiting, Semantic segmentation, Pattern recognition BibRef

Wang, L.T.[Lu-Ting], Li, X.J.[Xiao-Jie], Liao, Y.[Yue], Jiang, Z.[Zeren], Wu, J.L.[Jian-Long], Wang, F.[Fei], Qian, C.[Chen], Liu, S.[Si],
HEAD: HEtero-Assists Distillation for Heterogeneous Object Detectors,
ECCV22(IX:314-331).
Springer DOI 2211
BibRef

Chen, Z.Z.[Zhao-Zheng], Wang, T.[Tan], Wu, X.W.[Xiong-Wei], Hua, X.S.[Xian-Sheng], Zhang, H.W.[Han-Wang], Sun, Q.[Qianru],
Class Re-Activation Maps for Weakly-Supervised Semantic Segmentation,
CVPR22(959-968)
IEEE DOI 2210
Codes, Shape, Computational modeling, Semantics, Benchmark testing, Feature extraction, Recognition: detection, categorization, grouping and shape analysis BibRef

Xie, J.H.[Jin-Heng], Hou, X.X.[Xian-Xu], Ye, K.[Kai], Shen, L.L.[Lin-Lin],
CLIMS: Cross Language Image Matching for Weakly Supervised Semantic Segmentation,
CVPR22(4473-4482)
IEEE DOI 2210
Image segmentation, Codes, Shape, Image matching, Semantics, Natural languages, Segmentation, grouping and shape analysis, Vision + language BibRef

Chen, Z.[Zhang], Tian, Z.Q.[Zhi-Qiang], Zhu, J.[Jihua], Li, C.[Ce], Du, S.Y.[Shao-Yi],
C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical Image,
CVPR22(11666-11675)
IEEE DOI 2210
Training, Chaos, Image segmentation, Codes, Semantics, Anatomical structure, Segmentation, grouping and shape analysis BibRef

Li, J.[Jing], Fan, J.S.[Jun-Song], Zhang, Z.X.[Zhao-Xiang],
Towards Noiseless Object Contours for Weakly Supervised Semantic Segmentation,
CVPR22(16835-16844)
IEEE DOI 2210
Training, Location awareness, Image segmentation, Semantics, Refining, Predictive models, Scene analysis and understanding, grouping and shape analysis BibRef

Du, Y.[Ye], Fu, Z.[Zehua], Liu, Q.J.[Qing-Jie], Wang, Y.H.[Yun-Hong],
Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast,
CVPR22(4310-4319)
IEEE DOI 2210
Image segmentation, Shape, Semantics, Prototypes, Estimation, Pattern recognition, Segmentation, grouping and shape analysis BibRef

Xie, J.H.[Jin-Heng], Xiang, J.F.[Jian-Feng], Chen, J.L.[Jun-Liang], Hou, X.X.[Xian-Xu], Zhao, X.D.[Xiao-Dong], Shen, L.L.[Lin-Lin],
C2 AM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation,
CVPR22(979-988)
IEEE DOI 2210
Location awareness, Image segmentation, Codes, Shape, Semantics, Force, Recognition: detection, categorization, retrieval, Segmentation, Self- semi- meta- unsupervised learning BibRef

Sun, W.X.[Wei-Xuan], Zhang, J.[Jing], Barnes, N.M.[Nick M.],
Inferring the Class Conditional Response Map for Weakly Supervised Semantic Segmentation,
WACV22(2653-2662)
IEEE DOI 2202
Training, Image segmentation, Semantics, Pipelines, Inference algorithms, Cams, Segmentation, Grouping and Shape BibRef

Wu, T.[Tong], Huang, J.[Junshi], Gao, G.Y.[Guang-Yu], Wei, X.M.[Xiao-Ming], Wei, X.L.[Xiao-Lin], Luo, X.[Xuan], Liu, C.H.[Chi Harold],
Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation,
CVPR21(16760-16769)
IEEE DOI 2111
Image segmentation, Codes, Annotations, Semantics, Collaboration, Feature extraction BibRef

Oh, Y.[Youngmin], Kim, B.[Beomjun], Ham, B.[Bumsub],
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation,
CVPR21(6909-6918)
IEEE DOI 2111
Training, Image segmentation, Annotations, Computational modeling, Semantics, Feature extraction BibRef

Liu, Z.Z.[Zheng-Zhe], Qi, X.J.[Xiao-Juan], Fu, C.W.[Chi-Wing],
One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation,
CVPR21(1726-1736)
IEEE DOI 2111
Training, Annotations, Semantics, Training data, Prototypes BibRef

Neven, R.[Robby], Neven, D.[Davy], de Brabandere, B.[Bert], Proesmans, M.[Marc], Goedemé, T.[Toon],
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty,
ILDAV21(1678-1686)
IEEE DOI 2112
Training, Deep learning, Image segmentation, Uncertainty, Semantics, Neural networks BibRef

Yin, J.H.[Jun-Hui], Zhang, S.Q.[Si-Qing], Chang, D.L.[Dong-Liang], Ma, Z.Y.[Zhan-Yu], Guo, J.[Jun],
Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization,
ICPR21(4229-4236)
IEEE DOI 2105
weakly supervised object localization. Location awareness, Training, Deep learning, Adaptation models, Visualization, Automobiles BibRef

Cao, T.Y.[Tian-Yue], Du, L.Y.[Lian-Yu], Zhang, X.Y.[Xiao-Yun], Chen, S.H.[Si-Heng], Zhang, Y.[Ya], Wang, Y.F.[Yan-Feng],
CaT: Weakly Supervised Object Detection with Category Transfer,
ICCV21(3050-3059)
IEEE DOI 2203
Convolutional codes, Bridges, Semantics, Object detection, Detectors, Knowledge transfer, Detection and localization in 2D and 3D, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Yamazaki, M.[Masaki], Peng, X.C.[Xing-Chao], Saito, K.[Kuniaki], Hu, P.[Ping], Saenko, K.[Kate], Taniguchi, Y.[Yasuhiro],
Weakly Supervised Domain Adaptation using Super-pixel labeling for Semantic Segmentation,
MVA21(1-5)
DOI Link 2109
Deep learning, Image segmentation, Adaptation models, Annotations, Semantics, Object segmentation, Data models BibRef

Watanabe, K.[Kohei], Saito, K.[Kuniaki], Ushiku, Y.[Yoshitaka], Harada, T.[Tatsuya],
Multichannel Semantic Segmentation with Unsupervised Domain Adaptation,
AutoNUE18(V:600-616).
Springer DOI 1905
BibRef

Zhang, T.Y.[Tian-Yi], Lin, G.S.[Guo-Sheng], Liu, W.D.[Wei-De], Cai, J.F.[Jian-Fei], Kot, A.[Alex],
Splitting Vs. Merging: Mining Object Regions with Discrepancy and Intersection Loss for Weakly Supervised Semantic Segmentation,
ECCV20(XXII:663-679).
Springer DOI 2011
BibRef

Fan, J.S.[Jun-Song], Zhang, Z.X.[Zhao-Xiang], Tan, T.N.[Tie-Niu],
Employing Multi-estimations for Weakly-supervised Semantic Segmentation,
ECCV20(XVII:332-348).
Springer DOI 2011
BibRef

Chang, Y., Wang, Q., Hung, W., Piramuthu, R., Tsai, Y., Yang, M.,
Weakly-Supervised Semantic Segmentation via Sub-Category Exploration,
CVPR20(8988-8997)
IEEE DOI 2008
Task analysis, Feature extraction, Semantics, Training, Image segmentation, Computational modeling BibRef

Fan, J., Zhang, Z., Song, C., Tan, T.,
Learning Integral Objects With Intra-Class Discriminator for Weakly-Supervised Semantic Segmentation,
CVPR20(4282-4291)
IEEE DOI 2008
Image segmentation, Semantics, Training, Task analysis, Manifolds, Estimation, Benchmark testing BibRef

Zareian, A., Karaman, S., Chang, S.,
Weakly Supervised Visual Semantic Parsing,
CVPR20(3733-3742)
IEEE DOI 2008
Semantics, Visualization, Proposals, Image edge detection, Message passing, Task analysis BibRef

Yu, Z., Zhuge, Y., Lu, H., Zhang, L.,
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation,
ICCV19(7222-7232)
IEEE DOI 2004
image classification, image coding, image recognition, image segmentation, object detection, supervised learning, WSSS, Computational modeling BibRef

Marin, D.[Dmitrii], Boykov, Y.Y.[Yuri Y.],
Robust Trust Region for Weakly Supervised Segmentation,
ICCV21(6588-6598)
IEEE DOI 2203
Training, Deep learning, Image segmentation, Semantics, Neural networks, Training data, Vision applications and systems BibRef

Shen, Y.H.[Yun-Hang], Cao, L.J.[Liu-Juan], Chen, Z.W.[Zhi-Wei], Zhang, B.C.[Bao-Chang], Su, C.[Chi], Wu, Y.J.[Yong-Jian], Huang, F.Y.[Fei-Yue], Ji, R.R.[Rong-Rong],
Parallel Detection-and-Segmentation Learning for Weakly Supervised Instance Segmentation,
ICCV21(8178-8188)
IEEE DOI 2203
Training, Image segmentation, Correlation, Pipelines, Coherence, Object detection, Transfer/Low-shot/Semi/Unsupervised Learning, grouping and shape BibRef

Shen, Y.H.[Yun-Hang], Ji, R.R.[Rong-Rong], Wang, Y.[Yan], Wu, Y.J.[Yong-Jian], Cao, L.J.[Liu-Juan],
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation,
CVPR19(697-707).
IEEE DOI 2002
BibRef

Vernaza, P., Chandraker, M.,
Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation,
CVPR17(2953-2961)
IEEE DOI 1711
Image edge detection, Image segmentation, Labeling, Semantics, Training, Uncertainty BibRef

Xing, F.Z., Cambria, E., Huang, W.B., Xu, Y.,
Weakly supervised semantic segmentation with superpixel embedding,
ICIP16(1269-1273)
IEEE DOI 1610
Context BibRef

Pourian, N., Karthikeyan, S., Manjunath, B.S.,
Weakly Supervised Graph Based Semantic Segmentation by Learning Communities of Image-Parts,
ICCV15(1359-1367)
IEEE DOI 1602
Correlation BibRef

Zhang, W.[Wei], Zeng, S.[Sheng], Wang, D.[Dequan], Xue, X.Y.[Xiang-Yang],
Weakly supervised semantic segmentation for social images,
CVPR15(2718-2726)
IEEE DOI 1510
BibRef

Ying, P.[Peng], Liu, J.[Jing], Lu, H.Q.[Han-Qing],
Dictionary learning based superpixels clustering for weakly-supervised semantic segmentation,
ICIP15(4258-4262)
IEEE DOI 1512
Weak supervision;dictionary learning;semantic segmentation BibRef

Liu, Y.[Yang], Liu, J.[Jing], Li, Z.C.[Ze-Chao], Tang, J.H.[Jin-Hui], Lu, H.Q.[Han-Qing],
Weakly-Supervised Dual Clustering for Image Semantic Segmentation,
CVPR13(2075-2082)
IEEE DOI 1309
Image Semantic Segmentation; Weakly-Supervised BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Semi-Supervised Semantic Segmentation .


Last update:May 23, 2024 at 14:31:23