8.6.1.1 Weakly Supervised Instance Segmentation

Chapter Contents (Back)
Instance Segmentation. Segmentation, Guided. Segmentation, Instance. Weakly Supervised. 2604

See also Instance Segmentation.

Wang, L.T.[Lian-Tao], Meng, D., Hu, X.L.[Xue-Lei], Lu, J.F.[Jian-Feng], Zhao, J.[Ji],
Instance Annotation via Optimal BoW for Weakly Supervised Object Localization,
Cyber(47), No. 5, May 2017, pp. 1313-1324.
IEEE DOI 1704
BibRef
Earlier: A1, A5, A3, A4, Only:
Weakly supervised object localization via maximal entropy randomwalk,
ICIP14(1614-1617)
IEEE DOI 1502
Birds. Entropy BibRef

Hu, Z.[Zheng], Liu, Z.[Zhi], Li, G.Y.[Gong-Yang], Ye, L.W.[Lin-Wei], Zhou, L.[Lei], Wang, Y.[Yang],
Weakly supervised instance segmentation using multi-stage erasing refinement and saliency-guided proposals ordering,
JVCIR(73), 2020, pp. 102957.
Elsevier DOI 2012
Weakly supervised instance segmentation, Image-level annotations, Multi-stage erasing refinement, Saliency-guided proposals ordering BibRef

Xu, Y.Q.[Yun-Qiu], Zhou, C.L.[Chun-Luan], Yu, X.[Xin], Xiao, B.[Bin], Yang, Y.[Yi],
Pyramidal Multiple Instance Detection Network With Mask Guided Self-Correction for Weakly Supervised Object Detection,
IP(30), 2021, pp. 3029-3040.
IEEE DOI 2102
Proposals, Annotations, Object detection, Training, Image segmentation, Detectors, Task analysis, pyramidal network BibRef

Liu, Y.[Yun], Wu, Y.H.[Yu-Huan], Wen, P.S.[Pei-Song], Shi, Y.J.[Yu-Jun], Qiu, Y.[Yu], Cheng, M.M.[Ming-Ming],
Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation,
PAMI(44), No. 3, March 2022, pp. 1415-1428.
IEEE DOI 2202
Semantics, Proposals, Image segmentation, Training, Probability distribution, Feature extraction, Noise measurement, multi-way cut BibRef

Hao, S.Y.[Sheng-Yu], Wang, G.A.[Gao-Ang], Gu, R.S.[Ren-Shu],
Weakly supervised instance segmentation using multi-prior fusion,
CVIU(211), 2021, pp. 103261.
Elsevier DOI 2110
Instance segmentation, Weakly supervised, Multi-priors, Bounding box annotations BibRef

Zhang, J.B.[Jia-Bin], Su, H.[Hu], He, Y.H.[Yong-Hao], Zou, W.[Wei],
Weakly Supervised Instance Segmentation via Category-aware Centerness Learning with Localization Supervision,
PR(136), 2023, pp. 109165.
Elsevier DOI 2301
Weakly supervised learning, Instance segmentation, Centerness, Coarse localization annotation BibRef

Zhang, K.[Ke], Yuan, C.[Chun], Zhu, Y.M.[Yi-Ming], Jiang, Y.[Yong], Luo, L.[Lishu],
Weakly Supervised Instance Segmentation by Exploring Entire Object Regions,
MultMed(25), 2023, pp. 352-363.
IEEE DOI 2302
Image segmentation, Semantics, Task analysis, Streaming media, Location awareness, Saliency detection, Training, integration module BibRef

Zhu, L.J.[Liang-Jun], Peng, L.[Li], Ding, S.C.[Shu-Chen], Liu, Z.R.[Zhong-Ren],
An encoder-decoder framework with dynamic convolution for weakly supervised instance segmentation,
IET-CV(17), No. 8, 2023, pp. 883-894.
DOI Link 2312
image segmentation, object detection BibRef

Ji, Z.L.[Zong-Liang], Veksler, O.[Olga],
Regularized Loss With Hyperparameter Estimation for Weakly Supervised Single Class Segmentation,
PAMI(46), No. 5, May 2024, pp. 3923-3937.
IEEE DOI 2404
BibRef
Earlier: A2, Only:
Regularized Loss for Weakly Supervised Single Class Semantic Segmentation,
ECCV20(XXIX: 348-365).
Springer DOI 2010
Training, Cams, Conditional random fields, Task analysis, Semantic segmentation, Annotations, Annealing, Co-segmentation, weak supervision BibRef

Huang, Z.X.[Zu-Xian], Pan, D.S.[Dong-Sheng], Wu, G.S.[Gang-Shan],
Weakly supervised instance segmentation via peak mining and filtering,
IET-IPR(18), No. 6, 2024, pp. 1565-1578.
DOI Link 2405
image segmentation BibRef

Peng, J.[Jin], Wang, Y.X.[Yong-Xiong], Pan, Z.Q.[Zhi-Qun],
Weakly supervised instance segmentation via class double-activation maps and boundary localization,
SP:IC(127), 2024, pp. 117150.
Elsevier DOI 2408
Weakly supervised learning, Instance segmentation, Class double-activation map (double-CAM), Boundary localization BibRef


Kweon, H.[Hyeokjun], Yoon, K.J.[Kuk-Jin],
WISH: Weakly Supervised Instance Segmentation using Heterogeneous Labels,
CVPR25(25377-25387)
IEEE DOI 2508
Instance segmentation, Weak supervision, Costs, Annotations, weakly supervised instance segmentation, foundation model BibRef

Jiang, S.H.[Shang-Hang], Zhao, S.C.[Shi-Chao], Wu, M.[Meng], Zhang, L.[Le], Zhou, F.[Feng],
Overlap Loss: Rethinking Weakly Supervised Instance Segmentation in Crowded Scenes,
ICIP23(2905-2909)
IEEE DOI Code:
WWW Link. 2312
BibRef

Tang, L.[Linghua], Hui, L.[Le], Xie, J.[Jin],
Learning Inter-superpoint Affinity for Weakly Supervised 3d Instance Segmentation,
ACCV22(I:176-192).
Springer DOI 2307
BibRef

Lan, S.Y.[Shi-Yi], Yu, Z.D.[Zhi-Ding], Choy, C.[Christopher], Radhakrishnan, S.[Subhashree], Liu, G.L.[Gui-Lin], Zhu, Y.K.[Yu-Ke], Davis, L.S.[Larry S.], Anandkumar, A.[Anima],
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision,
ICCV21(3386-3396)
IEEE DOI 2203
Symbiosis, Measurement, Semantics, Benchmark testing, Real-time systems, Detection and localization in 2D and 3D, grouping and shape BibRef

Biertimpel, D.[David], Shkodrani, S.[Sindi], Baslamisli, A.S.[Anil S.], Baka, N.[Nóra],
Prior to Segment: Foreground Cues for Weakly Annotated Classes in Partially Supervised Instance Segmentation,
ICCV21(2804-2813)
IEEE DOI 2203
Training, Head, Cams, Detection and localization in 2D and 3D, Scene analysis and understanding BibRef

Yang, Y.Y.[Yu-Yuan], Hou, Y.L.[Ya-Li], Hou, Z.J.[Zhi-Jiang], Hao, X.L.[Xiao-Li], Shen, Y.[Yan],
Image-Level Supervised Instance Segmentation Using Instance-Wise Boundary,
ICIP21(1069-1073)
IEEE DOI 2201
Image segmentation, Annotations, Cams, Data mining, Instance segmentation, Weakly supervised, Image-level supervision BibRef

Wang, X.G.[Xing-Gang], Feng, J.[Jiapei], Hu, B.[Bin], Ding, Q.[Qi], Ran, L.J.[Long-Jin], Chen, X.X.[Xiao-Xin], Liu, W.Y.[Wen-Yu],
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient Images,
CVPR21(10220-10230)
IEEE DOI 2111
Training, Location awareness, Learning systems, Image segmentation, Codes, Merging BibRef

Lee, J.[Jungbeom], Yi, J.[Jihun], Shin, C.[Chaehun], Yoon, S.[Sungroh],
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation,
CVPR21(2643-2651)
IEEE DOI 2111
Image segmentation, Annotations, Semantics, Detectors, Benchmark testing, Generators BibRef

Hwang, J.[Jaedong], Kim, S.[Seohyun], Son, J.[Jeany], Han, B.H.[Bo-Hyung],
Weakly Supervised Instance Segmentation by Deep Community Learning,
WACV21(1019-1028)
IEEE DOI 2106
Training, Neural networks, Semantics, Object detection, Detectors, Feature extraction, Proposals BibRef

Arun, A.[Aditya], Jawahar, C.V., Kumar, M.P.[M. Pawan],
Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances,
ECCV20(XXVIII:254-270).
Springer DOI 2011
BibRef

Ge, W., Huang, W., Guo, S., Scott, M.,
Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation,
ICCV19(3344-3353)
IEEE DOI 2004
image classification, image representation, image segmentation, learning (artificial intelligence), object detection, Task analysis BibRef

Fan, R.C.[Ruo-Chen], Hou, Q.B.[Qi-Bin], Cheng, M.M.[Ming-Ming], Yu, G.[Gang], Martin, R.R.[Ralph R.], Hu, S.M.[Shi-Min],
Associating Inter-image Salient Instances for Weakly Supervised Semantic Segmentation,
ECCV18(IX: 371-388).
Springer DOI 1810
BibRef

Zhou, Y.Z.[Yan-Zhao], Zhu, Y.[Yi], Ye, Q.X.[Qi-Xiang], Qiu, Q.[Qiang], Jiao, J.B.[Jian-Bin],
Weakly Supervised Instance Segmentation Using Class Peak Response,
CVPR18(3791-3800)
IEEE DOI 1812
Image segmentation, Visualization, Training, Semantics, Proposals, Image color analysis, Kernel BibRef

Vezhnevets, A.[Alexander], Ferrari, V.[Vittorio], Buhmann, J.M.[Joachim M.],
Weakly supervised structured output learning for semantic segmentation,
CVPR12(845-852).
IEEE DOI 1208
BibRef
Earlier:
Weakly supervised semantic segmentation with a multi-image model,
ICCV11(643-650).
IEEE DOI 1201
BibRef

Vezhnevets, A.[Alexander], Buhmann, J.M.[Joachim M.],
Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning,
CVPR10(3249-3256).
IEEE DOI 1006

See also Agnostic Domain Adaptation. BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Single-Shot, Few-Shot Instance Segmentation .


Last update:Apr 18, 2026 at 20:43:46