8.3.4.3.3 Generative Adversarial Network, GAN, Semantic Segmentation

Chapter Contents (Back)
Generative Adversarial Network. Adversarial Network. Neural Networks. Semantic Segmentation. GAN.

Wei, Y.C.[Yun-Chao], Liang, X.D.[Xiao-Dan], Chen, Y.P.[Yun-Peng], Shen, X., Cheng, M.M., Feng, J., Zhao, Y.[Yao], Yan, S.C.[Shui-Cheng],
STC: A Simple to Complex Framework for Weakly-Supervised Semantic Segmentation,
PAMI(39), No. 11, November 2017, pp. 2314-2320.
IEEE DOI 1710
Benchmark testing, Image segmentation, Neural networks, Object detection, Semantics, Training, Semantic segmentation, convolutional neural network, weakly-supervised learning BibRef

Wei, Y.C.[Yun-Chao], Feng, J., Liang, X.D.[Xiao-Dan], Cheng, M.M., Zhao, Y.[Yao], Yan, S.C.[Shui-Cheng],
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach,
CVPR17(6488-6496)
IEEE DOI 1711
Head, Heating systems, Image segmentation, Proposals, Semantics, Training BibRef

Bi, L.[Lei], Feng, D.[Dagan], Kim, J.M.[Jin-Man],
Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation,
VC(34), No. 6-8, June 2018, pp. 1043-1052.
WWW Link. 1806
BibRef

Zhu, X.O.[Xia-Obin], Zhang, X.M.[Xin-Ming], Zhang, X.Y.[Xiao-Yu], Xue, Z.[Ziyu], Wang, L.[Lei],
A novel framework for semantic segmentation with generative adversarial network,
JVCIR(58), 2019, pp. 532-543.
Elsevier DOI 1901
Semantic segmentation, Generative adversarial network (GAN), Wasserstein distance, Auxiliary higher-order potential loss BibRef

Benjdira, B.[Bilel], Bazi, Y.[Yakoub], Koubaa, A.[Anis], Ouni, K.[Kais],
Unsupervised Domain Adaptation Using Generative Adversarial Networks for Semantic Segmentation of Aerial Images,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Wang, Q., Gao, J., Li, X.,
Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes,
IP(28), No. 9, Sep. 2019, pp. 4376-4386.
IEEE DOI 1908
convolutional neural nets, feature extraction, image classification, image segmentation, weakly supervision BibRef

Qiu, S., Zhao, Y., Jiao, J., Wei, Y., Wei, S.,
Referring Image Segmentation by Generative Adversarial Learning,
MultMed(22), No. 5, May 2020, pp. 1333-1344.
IEEE DOI 2005
Image segmentation, Semantics, Feature extraction, Natural languages, Generators, Generative adversarial networks, Adversarial training BibRef

di Mauro, D.[Daniele], Furnari, A.[Antonino], Patanč, G.[Giuseppe], Battiato, S.[Sebastiano], Farinella, G.M.[Giovanni Maria],
SceneAdapt: Scene-based domain adaptation for semantic segmentation using adversarial learning,
PRL(136), 2020, pp. 175-182.
Elsevier DOI 2008
Semantic segmentation, Domain adaptation, Scene adaptation, Adversarial learning, BibRef

Arnab, A., Miksik, O., Torr, P.H.S.,
On the Robustness of Semantic Segmentation Models to Adversarial Attacks,
PAMI(42), No. 12, December 2020, pp. 3040-3053.
IEEE DOI 2011
BibRef
Earlier: CVPR18(888-897)
IEEE DOI 1812
Robustness, Semantics, Image segmentation, Perturbation methods, Deep learning, Neural networks, Image recognition, machine learning security. Task analysis, Training BibRef

Wang, Y.D.[Yi-Dong], Mo, L.[Lisha], Ma, H.M.[Hui-Min], Yuan, J.[Jian],
OccGAN: Semantic image augmentation for driving scenes,
PRL(136), 2020, pp. 257-263.
Elsevier DOI 2008
Occlusion, GAN, Semantic, Augmentation, Cityscapes BibRef

Tasar, O., Happy, S.L., Tarabalka, Y., Alliez, P.,
ColorMapGAN: Unsupervised Domain Adaptation for Semantic Segmentation Using Color Mapping Generative Adversarial Networks,
GeoRS(58), No. 10, October 2020, pp. 7178-7193.
IEEE DOI 2009
Training, Remote sensing, Image segmentation, Training data, Semantics, Image color analysis, Generative adversarial networks, semantic segmentation BibRef

Tasar, O., Tarabalka, Y., Giros, A., Alliez, P., Clerc, S.,
StandardGAN: Multi-source Domain Adaptation for Semantic Segmentation of Very High Resolution Satellite Images by Data Standardization,
EarthVision20(747-756)
IEEE DOI 2008
Urban areas, Generators, Remote sensing, Task analysis, Semantics, Image segmentation BibRef

Toldo, M.[Marco], Michieli, U.[Umberto], Agresti, G.[Gianluca], Zanuttigh, P.[Pietro],
Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment,
IVC(95), 2020, pp. 103889.
Elsevier DOI 2004
Unsupervised domain adaptation, Semantic segmentation, Adversarial learning, Transfer learning, Image-to-image translation BibRef

Huang, W.[Wei], Shao, Z.F.[Zhan-Fei], Luo, M.Y.[Ming-Yuan], Zhang, P.[Peng], Zha, Y.F.[Yu-Fei],
A novel multi-loss-based deep adversarial network for handling challenging cases in semi-supervised image semantic segmentation,
PRL(146), 2021, pp. 208-214.
Elsevier DOI 2105
Image semantic segmentation, Semi-supervised learning, Deep adversarial network BibRef

Mittal, S.[Sudhanshu], Tatarchenko, M.[Maxim], Brox, T.[Thomas],
Semi-Supervised Semantic Segmentation With High- and Low-Level Consistency,
PAMI(43), No. 4, April 2021, pp. 1369-1379.
IEEE DOI 2103
Image segmentation, Training, Semantics, Generators, Standards, Semisupervised learning, generative adversarial networks BibRef

Bai, X.[Xing], Zhou, J.[Jun],
Parallel global convolutional network for semantic image segmentation,
IET-IPR(15), No. 1, 2021, pp. 252-259.
DOI Link 2106
BibRef

Zhang, J.[Jia], Li, Z.X.[Zhi-Xin], Zhang, C.L.[Can-Long], Ma, H.F.[Hui-Fang],
Stable self-attention adversarial learning for semi-supervised semantic image segmentation,
JVCIR(78), 2021, pp. 103170.
Elsevier DOI 2107
BibRef
Earlier:
Robust Adversarial Learning For Semi-Supervised Semantic Segmentation,
ICIP20(728-732)
IEEE DOI 2011
Self-Attention Mechanism, Adversarial Learning, Semi-Supervised Learning, Spectral Normalization, Semantic Image Segmentation. Training, Semantics, Image segmentation, Generative adversarial networks, Lips, Generators, Self-Attention, Spectral Normalization BibRef

Jamali-Rad, H.[Hadi], Szabó, A.[Attila],
Lookahead adversarial learning for near real-time semantic segmentation,
CVIU(212), 2021, pp. 103271.
Elsevier DOI 2110
Semantic segmentation, Conditional adversarial training, Deep learning BibRef

Huang, J.X.[Jia-Xing], Guan, D.[Dayan], Xiao, A.[Aoran], Lu, S.J.[Shi-Jian],
Multi-level adversarial network for domain adaptive semantic segmentation,
PR(123), 2022, pp. 108384.
Elsevier DOI 2112
Unsupervised domain adaptation, Semantic segmentation, Adversarial learning, Self training BibRef

Wang, W.[Wen], Zhang, J.[Jing], Zhai, W.[Wei], Cao, Y.[Yang], Tao, D.C.[Da-Cheng],
Robust Object Detection via Adversarial Novel Style Exploration,
IP(31), 2022, pp. 1949-1962.
IEEE DOI 2202
Degradation, Compounds, Training, Object detection, Adaptation models, Task analysis, Image enhancement, adversarial learning BibRef

Luo, Y.[Yawei], Liu, P.[Ping], Zheng, L.[Liang], Guan, T.[Tao], Yu, J.Q.[Jun-Qing], Yang, Y.[Yi],
Category-Level Adversarial Adaptation for Semantic Segmentation Using Purified Features,
PAMI(44), No. 8, August 2022, pp. 3940-3956.
IEEE DOI 2207
Semantics, Task analysis, Training, Loss measurement, Feature extraction, Visualization, Computer science, information bottleneck BibRef

Wang, D.[Derui], Li, C.[Chaoran], Wen, S.[Sheng], Han, Q.L.[Qing-Long], Nepal, S.[Surya], Zhang, X.Y.[Xiang-Yu], Xiang, Y.[Yang],
Daedalus: Breaking Nonmaximum Suppression in Object Detection via Adversarial Examples,
Cyber(52), No. 8, August 2022, pp. 7427-7440.
IEEE DOI 2208
Task analysis, Perturbation methods, Biological system modeling, Load modeling, Feature extraction, Computational modeling, object detection (OD) BibRef


Kassapis, E.[Elias], Dikov, G.[Georgi], Gupta, D.K.[Deepak K.], Nugteren, C.[Cedric],
Calibrated Adversarial Refinement for Stochastic Semantic Segmentation,
ICCV21(7037-7047)
IEEE DOI 2203
Uncertainty, Semantics, Toy manufacturing industry, Stochastic processes, Probabilistic logic, Robustness, Vision applications and systems BibRef

Xu, X.G.[Xiao-Gang], Zhao, H.[Hengshuang], Jia, J.Y.[Jia-Ya],
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation,
ICCV21(7466-7475)
IEEE DOI 2203
Training, Costs, Computational modeling, Perturbation methods, Semantics, Neural networks, Robustness, Segmentation, Adversarial learning BibRef

Kim, D.[Dahye], Hong, B.W.[Byung-Woo],
Unsupervised Segmentation incorporating Shape Prior via Generative Adversarial Networks,
ICCV21(7304-7314)
IEEE DOI 2203
Deep learning, Image segmentation, Shape, Lighting, Benchmark testing, Generative adversarial networks, Segmentation, Neural generative models BibRef

Kugelman, J.[Jason], Alonso-Caneiro, D.[David], Read, S.A.[Scott A.], Vincent, S.J.[Stephen J.], Chen, F.K.[Fred K.], Collins, M.J.[Michael J.],
Dual image and mask synthesis with GANs for semantic segmentation in optical coherence tomography,
DICTA20(1-8)
IEEE DOI 2201
Training, Deep learning, Image segmentation, Optical coherence tomography, Semantics, neural networks BibRef

Li, D.Q.[Dai-Qing], Yang, J.L.[Jun-Lin], Kreis, K.[Karsten], Torralba, A.B.[Antonio B.], Fidler, S.[Sanja],
Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization,
CVPR21(8296-8307)
IEEE DOI 2111
Training, Image segmentation, Annotations, Animals, Face recognition, Computational modeling, Semantics BibRef

He, J.Z.[Jian-Zhong], Jia, X.[Xu], Chen, S.[Shuaijun], Liu, J.Z.[Jian-Zhuang],
Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation,
CVPR21(11003-11012)
IEEE DOI 2111
Training, Image segmentation, Adaptation models, Semantics, Benchmark testing, Collaborative work BibRef

Isobe, T.[Takashi], Jia, X.[Xu], Chen, S.[Shuaijun], He, J.Z.[Jian-Zhong], Shi, Y.J.[Yong-Jie], Liu, J.Z.[Jian-Zhuang], Lu, H.C.[Hu-Chuan], Wang, S.J.[Sheng-Jin],
Multi-Target Domain Adaptation with Collaborative Consistency Learning,
CVPR21(8183-8192)
IEEE DOI 2111
Adaptation models, Image segmentation, Computational modeling, Semantics, Collaboration, Predictive models BibRef

Wang, H.R.[Hao-Ran], Shen, T.[Tong], Zhang, W.[Wei], Duan, L.Y.[Ling-Yu], Mei, T.[Tao],
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation,
ECCV20(XIV:642-659).
Springer DOI 2011
BibRef

Samson, L., van Noord, N., Booij, O., Hofmann, M., Gavves, E., Ghafoorian, M.,
I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation,
CVRSUAD19(951-960)
IEEE DOI 2004
image segmentation, learning (artificial intelligence), neural nets, object detection, pixel-wise metrics, Semantic segmentation BibRef

Ma, L.Y.[Lei-Yuan], Liu, Z.Y.[Zi-Yi], Zheng, N.N.[Nan-Ning], Wang, J.J.[Jian-Ji],
HAR Enhanced Weakly-Supervised Semantic Segmentation Coupled with Adversarial Learning,
ICIP19(1845-1849)
IEEE DOI 1910
semantic segmentation, weakly-supervised, adversarial learning, atrous rate BibRef

Choi, J., Kim, T., Kim, C.,
Self-Ensembling With GAN-Based Data Augmentation for Domain Adaptation in Semantic Segmentation,
ICCV19(6829-6839)
IEEE DOI 2004
image classification, image segmentation, neural nets, unsupervised learning, GAN-based data augmentation, Feature extraction BibRef

Shukla, S., Van Gool, L.J., Timofte, R.,
Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation,
AIM19(3368-3377)
IEEE DOI 2004
image classification, image segmentation, supervised learning, unsupervised learning, generative models, adversarial training, semi supervised learning BibRef

Saporta, A.[Antoine], Vu, T.H.[Tuan-Hung], Cord, M.[Matthieu], Pérez, P.[Patrick],
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation,
ICCV21(9052-9061)
IEEE DOI 2203
Adaptation models, Autonomous systems, Semantics, Adversarial machine learning, Task analysis, Knowledge transfer, Vision for robotics and autonomous vehicles BibRef

Vu, T.H.[Tuan-Hung], Jain, H.[Himalaya], Bucher, M.[Maxime], Cord, M.[Matthieu], Perez, P.[Patrick],
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation,
CVPR19(2512-2521).
IEEE DOI 2002
BibRef

Xiao, C.W.[Chao-Wei], Deng, R.Z.[Rui-Zhi], Li, B.[Bo], Yu, F.[Fisher], Liu, M.Y.[Ming-Yan], Song, D.[Dawn],
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation,
ECCV18(X: 220-237).
Springer DOI 1810
BibRef

Xie, C., Wang, J., Zhang, Z., Zhou, Y., Xie, L., Yuille, A.L.[Alan L.],
Adversarial Examples for Semantic Segmentation and Object Detection,
ICCV17(1378-1387)
IEEE DOI 1802
image classification, image segmentation, object detection, pattern clustering, adversarial perturbations, Semantics BibRef

Souly, N., Spampinato, C., Shah, M.,
Semi Supervised Semantic Segmentation Using Generative Adversarial Network,
ICCV17(5689-5697)
IEEE DOI 1802
feature extraction, image classification, image segmentation, learning (artificial intelligence), semantic networks, Visualization BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Encoder-Decoder Networks for Semantic Segmentation .


Last update:Aug 11, 2022 at 11:48:53