14.5.7.7 Adversarial Networks, Adversarial Inputs, Generative Adversarial

Chapter Contents (Back)
Adversarial Networks. Generative Networks. GAN. Deliberate noise to fool the network. Generative Adversarial Networks to generate images by countering the detection network. Also Attacks on NN based recognition. See also Recurrent Neural Networks for Shapes and Complex Features, RNN. See also Data Augmentation, Generative Network, Convolutional Network.

Tao, Y.T.[Yi-Ting], Xu, M.Z.[Miao-Zhong], Zhang, F.[Fan], Du, B.[Bo], Zhang, L.P.[Liang-Pei],
Unsupervised-Restricted Deconvolutional Neural Network for Very High Resolution Remote-Sensing Image Classification,
GeoRS(55), No. 12, December 2017, pp. 6805-6823.
IEEE DOI 1712
Use small number of labeled pixels. Data models, Deconvolution, Feature extraction, Image resolution, Remote sensing, Satellites, Training, very high resolution (VHR) image per-pixel classification BibRef

Hu, F.[Fan], Xia, G.S.[Gui-Song], Hu, J.W.[Jing-Wen], Zhang, L.P.[Liang-Pei],
Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery,
RS(7), No. 11, 2015, pp. 14680.
DOI Link 1512
BibRef

Tao, Y.T.[Yi-Ting], Xu, M.Z.[Miao-Zhong], Zhong, Y.F.[Yan-Fei], Cheng, Y.F.[Yu-Feng],
GAN-Assisted Two-Stream Neural Network for High-Resolution Remote Sensing Image Classification,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Xu, R.D.[Ru-Dong], Tao, Y.T.[Yi-Ting], Lu, Z.Y.[Zhong-Yuan], Zhong, Y.F.[Yan-Fei],
Attention-Mechanism-Containing Neural Networks for High-Resolution Remote Sensing Image Classification,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

He, Z.[Zhi], Liu, H.[Han], Wang, Y.[Yiwen], Hu, J.[Jie],
Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

He, Z.[Zhi], Wang, Y.[Yiwen], Hu, J.[Jie],
Joint Sparse and Low-Rank Multitask Learning with Laplacian-Like Regularization for Hyperspectral Classification,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Creswell, A., White, T., Dumoulin, V., Arulkumaran, K., Sengupta, B., Bharath, A.A.,
Generative Adversarial Networks: An Overview,
SPMag(35), No. 1, January 2018, pp. 53-65.
IEEE DOI 1801
Convolutional codes, Data models, Generators, Image resolution, Machine learning, Semantics, Signal resolution, Training data BibRef

Gao, F.[Fei], Yang, Y.[Yue], Wang, J.[Jun], Sun, J.P.[Jin-Ping], Yang, E.[Erfu], Zhou, H.Y.[Hui-Yu],
A Deep Convolutional Generative Adversarial Networks (DCGANs)-Based Semi-Supervised Method for Object Recognition in Synthetic Aperture Radar (SAR) Images,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Chang, W.[Wenkai], Yang, G.D.[Guo-Dong], Yu, J.[Junzhi], Liang, Z.[Zize],
Real-time segmentation of various insulators using generative adversarial networks,
IET-CV(12), No. 5, August 2018, pp. 596-602.
DOI Link 1807
BibRef

Huang, B.[Bin], Chen, W.H.[Wei-Hai], Wu, X.[Xingming], Lin, C.L.[Chun-Liang], Suganthan, P.N.[Ponnuthurai Nagaratnam],
High-quality face image generated with conditional boundary equilibrium generative adversarial networks,
PRL(111), 2018, pp. 72-79.
Elsevier DOI 1808
Super resolution, Generative Adversarial Network (GAN), Face hallucination, Convolutional Neural Network (CNN) BibRef

Biggio, B.[Battista], Roli, F.[Fabio],
Wild patterns: Ten years after the rise of adversarial machine learning,
PR(84), 2018, pp. 317-331.
Elsevier DOI 1809
Adversarial machine learning, Evasion attacks, Poisoning attacks, Adversarial examples, Secure learning, Deep learning BibRef

Zhu, L., Chen, Y., Ghamisi, P., Benediktsson, J.A.,
Generative Adversarial Networks for Hyperspectral Image Classification,
GeoRS(56), No. 9, September 2018, pp. 5046-5063.
IEEE DOI 1809
Training, Hyperspectral imaging, Feature extraction, Generators, hyperspectral image (HSI) classification BibRef

Tan, W.R., Chan, C.S., Aguirre, H.E., Tanaka, K.,
Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork,
IP(28), No. 1, January 2019, pp. 394-409.
IEEE DOI 1810
Generators, Image generation, Image quality, Generative adversarial networks, Training, Image resolution, ArtGAN BibRef

Chen, X., Xu, C., Yang, X., Song, L., Tao, D.,
Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer,
IP(28), No. 2, February 2019, pp. 546-560.
IEEE DOI 1811
codecs, image classification, image coding, image reconstruction, rendering (computer graphics), Gated-GAN, adversarial generative networks BibRef

Zheng, R.B.[Ruo-Bing], Wu, G.Q.[Guo-Qiang], Yan, C.[Chao], Zhang, R.[Renyu], Luo, Z.[Ze], Yan, B.P.[Bao-Ping],
Exploration in Mapping Kernel-Based Home Range Models from Remote Sensing Imagery with Conditional Adversarial Networks,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Zhang, L., Gonzalez-Garcia, A., van de Weijer, J.[Joost], Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz],
Synthetic Data Generation for End-to-End Thermal Infrared Tracking,
IP(28), No. 4, April 2019, pp. 1837-1850.
IEEE DOI 1901
convolution, feature extraction, feedforward neural nets, image colour analysis, image motion analysis, image sequences, generative networks BibRef

Liu, X.L.[Xia-Lei], van de Weijer, J.[Joost], Bagdanov, A.D.[Andrew D.],
Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank,
PAMI(41), No. 8, August 2019, pp. 1862-1878.
IEEE DOI 1907
Task analysis, Training, Image quality, Visualization, Uncertainty, Labeling, Neural networks, Learning from rankings, active learning BibRef

Wu, K.W.[Ke-Wei], Gao, Y.[Yang], Ma, H.L.[Hai-Long], Sun, Y.X.[Yong-Xuan], Yao, T.T.[Ting-Ting], Xie, Z.[Zhao],
A deep generative directed network for scene depth ordering,
JVCIR(58), 2019, pp. 554-564.
Elsevier DOI 1901
Deep generative directed-network, Depth ordering, Hidden Markov field, DenseNet See also Densely Connected Convolutional Networks. BibRef

Aggarwal, H.K.[Hemant K.], Mani, M.P.[Merry P.], Jacob, M.[Mathews],
MoDL: Model-Based Deep Learning Architecture for Inverse Problems,
MedImg(38), No. 2, February 2019, pp. 394-405.
IEEE DOI 1902
Image reconstruction, Training data, Training, Optimization, Imaging, Numerical models, Machine learning, Deep learning, convolutional neural network BibRef

Borji, A.[Ali],
Pros and cons of GAN evaluation measures,
CVIU(179), 2019, pp. 41-65.
Elsevier DOI 1903
Generative adversarial nets, Generative models, Evaluation, Deep learning, Neural networks BibRef

Li, Y.[Yi], Song, L.X.[Ling-Xiao], Wu, X.[Xiang], He, R.[Ran], Tan, T.N.[Tie-Niu],
Learning a bi-level adversarial network with global and local perception for makeup-invariant face verification,
PR(90), 2019, pp. 99-108.
Elsevier DOI 1903
Face verification, Makeup-invariant, Generative adversarial network BibRef

Ding, S.[Sihao], Wallin, A.[Andreas],
Towards recovery of conditional vectors from conditional generative adversarial networks,
PRL(122), 2019, pp. 66-72.
Elsevier DOI 1904
Generative adversarial networks, Conditional, Recover BibRef

Tran, L.[Linh], Kossaifi, J.[Jean], Panagakis, Y.[Yannis], Pantic, M.[Maja],
Disentangling Geometry and Appearance with Regularised Geometry-Aware Generative Adversarial Networks,
IJCV(127), No. 6-7, June 2019, pp. 824-844.
Springer DOI 1906
BibRef
Earlier: A2, A1, A3, A4:
GAGAN: Geometry-Aware Generative Adversarial Networks,
CVPR18(878-887)
IEEE DOI 1812
Shape, Geometry, Generators, Training, Computational modeling, Face BibRef

Chen, L.Q.[Liu-Qing], Wang, P.[Pan], Dong, H.[Hao], Shi, F.[Feng], Han, J.[Ji], Guo, Y.[Yike], Childs, P.R.N.[Peter R.N.], Xiao, J.[Jun], Wu, C.[Chao],
An artificial intelligence based data-driven approach for design ideation,
JVCIR(61), 2019, pp. 10-22.
Elsevier DOI 1906
Idea generation, Artificial intelligence in design, Data-driven design, Generative adversarial networks, Computational creativity BibRef

Miyato, T.[Takeru], Maeda, S.I.[Shin-Ichi], Koyama, M.[Masanori], Ishii, S.[Shin],
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning,
PAMI(41), No. 8, August 2019, pp. 1979-1993.
IEEE DOI 1907
Training, Perturbation methods, Artificial neural networks, Semisupervised learning, Data models, Computational modeling, deep learning BibRef

Deng, C., Yang, E., Liu, T., Li, J., Liu, W., Tao, D.,
Unsupervised Semantic-Preserving Adversarial Hashing for Image Search,
IP(28), No. 8, August 2019, pp. 4032-4044.
IEEE DOI 1907
binary codes, file organisation, image coding, image retrieval, matrix algebra, neural nets, unsupervised learning, deep learning BibRef

Yu, B., Zhou, L., Wang, L., Shi, Y., Fripp, J., Bourgeat, P.,
Ea-GANs: Edge-Aware Generative Adversarial Networks for Cross-Modality MR Image Synthesis,
MedImg(38), No. 7, July 2019, pp. 1750-1762.
IEEE DOI 1907
Image edge detection, Image generation, Generative adversarial networks, Generators, Imaging, brain BibRef


Nguyen, N.M., Ray, N.,
Generative Adversarial Networks Using Adaptive Convolution,
CRV19(129-134)
IEEE DOI 1908
Convolution, Generators, Generative adversarial networks, Training, Computer architecture, Adaptation models, Generative Adversarial Networks BibRef

Chen, K.[Kevin], Choy, C.B.[Christopher B.], Savva, M.[Manolis], Chang, A.X.[Angel X.], Funkhouser, T.[Thomas], Savarese, S.[Silvio],
Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings,
ACCV18(III:100-116).
Springer DOI 1906
Generating colored 3D shapes from natural language. BibRef

Vo, D.M.[Duc Minh], Sugimoto, A.[Akihiro],
Paired-D GAN for Semantic Image Synthesis,
ACCV18(IV:468-484).
Springer DOI 1906
BibRef

Ge, H.W.[Hong-Wei], Yao, Y.[Yao], Chen, Z.[Zheng], Sun, L.[Liang],
Unsupervised Transformation Network Based on GANs for Target-Domain Oriented Multi-Domain Image Translation,
ACCV18(II:398-413).
Springer DOI 1906
BibRef

Guo, W.K.[Wei-Kuo], Liang, J.[Jian], Kong, X.W.[Xiang-Wei], Song, L.X.[Ling-Xiao], He, R.[Ran],
X-GACMN: An X-Shaped Generative Adversarial Cross-Modal Network with Hypersphere Embedding,
ACCV18(V:513-529).
Springer DOI 1906
BibRef

Ying, G.H.[Guo-Hao], Zou, Y.T.[Ying-Tian], Wan, L.[Lin], Hu, Y.M.[Yi-Ming], Feng, J.[Jiashi],
Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks,
ACCV18(VI:277-292).
Springer DOI 1906
BibRef

Hsu, S.Y.[Shu-Yu], Yang, C.Y.[Chih-Yuan], Huang, C.C.[Chi-Chia], Hsu, J.Y.J.[Jane Yung-Jen],
SemiStarGAN: Semi-supervised Generative Adversarial Networks for Multi-domain Image-to-Image Translation,
ACCV18(IV:338-353).
Springer DOI 1906
BibRef

Heljakka, A.[Ari], Solin, A.[Arno], Kannala, J.H.[Ju-Ho],
Pioneer Networks: Progressively Growing Generative Autoencoder,
ACCV18(I:22-38).
Springer DOI 1906
BibRef

Alberti, M.[Michele], Pondenkandath, V.[Vinaychandran], Würsch, M.[Marcel], Bouillon, M.[Manuel], Seuret, M.[Mathias], Ingold, R.[Rolf], Liwicki, M.[Marcus],
Are You Tampering with My Data?,
Objectionable18(II:296-312).
Springer DOI 1905
BibRef

Belagiannis, V.[Vasileios], Farshad, A.[Azade], Galasso, F.[Fabio],
Adversarial Network Compression,
CEFR-LCV18(IV:431-449).
Springer DOI 1905
BibRef

Öngün, C.[Cihan], Temizel, A.[Alptekin],
Paired 3D Model Generation with Conditional Generative Adversarial Networks,
3D-Wild18(I:473-487).
Springer DOI 1905
BibRef

Croce, F.[Francesco], Hein, M.[Matthias],
A Randomized Gradient-Free Attack on ReLU Networks,
GCPR18(215-227).
Springer DOI 1905
BibRef

Taran, O.[Olga], Rezaeifar, S.[Shideh], Voloshynovskiy, S.[Slava],
Bridging Machine Learning and Cryptography in Defence Against Adversarial Attacks,
Objectionable18(II:267-279).
Springer DOI 1905
BibRef

Carrara, F.[Fabio], Becarelli, R.[Rudy], Caldelli, R.[Roberto], Falchi, F.[Fabrizio], Amato, G.[Giuseppe],
Adversarial Examples Detection in Features Distance Spaces,
Objectionable18(II:313-327).
Springer DOI 1905
BibRef

Assens, M.[Marc], Giro-i-Nieto, X.[Xavier], McGuinness, K.[Kevin], O'Connor, N.E.[Noel E.],
PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks,
Egocentric18(V:406-422).
Springer DOI 1905
BibRef

Wang, X.[Xintao], Yu, K.[Ke], Wu, S.[Shixiang], Gu, J.[Jinjin], Liu, Y.[Yihao], Dong, C.[Chao], Qiao, Y.[Yu], Loy, C.C.[Chen Change],
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks,
PerceptualRest18(V:63-79).
Springer DOI 1905
BibRef

Jaiswal, A.[Ayush], Abd-Almageed, W.[Wael], Wu, Y.[Yue], Natarajan, P.[Premkumar],
Bidirectional Conditional Generative Adversarial Networks,
ACCV18(III:216-232).
Springer DOI 1906
BibRef
Earlier:
CapsuleGAN: Generative Adversarial Capsule Network,
BrainDriven18(III:526-535).
Springer DOI 1905
BibRef

Blum, O.[Oliver], Brattoli, B.[Biagio], Ommer, B.[Björn],
X-GAN: Improving Generative Adversarial Networks with ConveX Combinations,
GCPR18(199-214).
Springer DOI 1905
BibRef

Zhao, W.[Wei], Yang, P.[Pengpeng], Ni, R.R.[Rong-Rong], Zhao, Y.[Yao], Li, W.J.[Wen-Jie],
Cycle GAN-Based Attack on Recaptured Images to Fool both Human and Machine,
IWDW18(83-92).
Springer DOI 1905
BibRef

Naseer, M., Khan, S., Porikli, F.,
Local Gradients Smoothing: Defense Against Localized Adversarial Attacks,
WACV19(1300-1307)
IEEE DOI 1904
data compression, feature extraction, gradient methods, image classification, image coding, image representation, High frequency BibRef

Kazemi, H., Iranmanesh, S.M., Nasrabadi, N.,
Style and Content Disentanglement in Generative Adversarial Networks,
WACV19(848-856)
IEEE DOI 1904
feature extraction, geophysical image processing, image classification, image representation, image texture, Task analysis BibRef

Han, T., Lu, Y., Wu, J., Xing, X., Wu, Y.N.,
Learning Generator Networks for Dynamic Patterns,
WACV19(809-818)
IEEE DOI 1904
convolutional neural nets, image representation, image sequences, learning (artificial intelligence), spatiotemporal phenomena, Dynamics BibRef

Shao, H.[Hang], Kumar, A.[Abhishek], Fletcher, P.T.[P. Thomas],
The Riemannian Geometry of Deep Generative Models,
Diff-CVML18(428-4288)
IEEE DOI 1812
Manifolds, Jacobian matrices, Computational modeling, Measurement, Geometry, Generators, Data models BibRef

Esser, P.[Patrick], Sutter, E.[Ekaterina],
A Variational U-Net for Conditional Appearance and Shape Generation,
CVPR18(8857-8866)
IEEE DOI 1812
Shape, Generators, Image generation, Standards, Image color analysis, Training, Footwear BibRef

Russo, P., Carlucci, F.M., Tommasi, T., Caputo, B.,
From Source to Target and Back: Symmetric Bi-Directional Adaptive GAN,
CVPR18(8099-8108)
IEEE DOI 1812
Generators, Training, Adaptation models, Image reconstruction, Bidirectional control, Image generation BibRef

Wang, S., Shi, Y., Han, Y.,
Universal Perturbation Generation for Black-box Attack Using Evolutionary Algorithms,
ICPR18(1277-1282)
IEEE DOI 1812
Perturbation methods, Evolutionary computation, Sociology, Statistics, Training, Neural networks, Robustness BibRef

Xu, X.J.[Xiao-Jun], Chen, X.Y.[Xin-Yun], Liu, C.[Chang], Rohrbach, A.[Anna], Darrell, T.J.[Trevor J.], Song, D.[Dawn],
Fooling Vision and Language Models Despite Localization and Attention Mechanism,
CVPR18(4951-4961)
IEEE DOI 1812
Attacks. Prediction algorithms, Computational modeling, Neural networks, Knowledge discovery, Visualization, Predictive models, Natural languages BibRef

Deshpande, I.[Ishan], Zhang, Z.Y.[Zi-Yu], Schwing, A.[Alexander],
Generative Modeling Using the Sliced Wasserstein Distance,
CVPR18(3483-3491)
IEEE DOI 1812
Training, Generators, Stability analysis, Optimization, Task analysis, Computational modeling BibRef

Juefei-Xu, F., Boddeti, V.N., Savvides, M.,
Perturbative Neural Networks,
CVPR18(3310-3318)
IEEE DOI 1812
Perturbation methods, Convolution, Standards, Task analysis, Convolutional neural networks, Visualization BibRef

Anoosheh, A., Agustsson, E., Timofte, R., Van Gool, L.J.,
ComboGAN: Unrestrained Scalability for Image Domain Translation,
Restoration18(896-8967)
IEEE DOI 1812
Training, Generators, Decoding, Computer vision, Task analysis, Data models BibRef

Song, Y., Ma, C., Wu, X., Gong, L., Bao, L., Zuo, W., Shen, C., Lau, R.W.H., Yang, M.,
VITAL: VIsual Tracking via Adversarial Learning,
CVPR18(8990-8999)
IEEE DOI 1812
Target tracking, Training, Feature extraction, Generators, Visualization, Entropy BibRef

Prakash, A., Moran, N., Garber, S., DiLillo, A., Storer, J.,
Deflecting Adversarial Attacks with Pixel Deflection,
CVPR18(8571-8580)
IEEE DOI 1812
Perturbation methods, Transforms, Minimization, Robustness, Noise reduction, Training, Computer vision BibRef

Oseledets, I., Khrulkov, V.,
Art of Singular Vectors and Universal Adversarial Perturbations,
CVPR18(8562-8570)
IEEE DOI 1812
Perturbation methods, Jacobian matrices, Optimization, Neural networks, Computer vision, Visualization, Correlation BibRef

Zhang, J., Ding, Z., Li, W., Ogunbona, P.,
Importance Weighted Adversarial Nets for Partial Domain Adaptation,
CVPR18(8156-8164)
IEEE DOI 1812
Feature extraction, Task analysis, Training, Games, Neural networks BibRef

Li, H., Pan, S.J., Wang, S., Kot, A.C.,
Domain Generalization with Adversarial Feature Learning,
CVPR18(5400-5409)
IEEE DOI 1812
Data models, Training, Training data, Adaptation models, Decoding, Predictive models BibRef

Zhang, W., Ouyang, W., Li, W., Xu, D.,
Collaborative and Adversarial Network for Unsupervised Domain Adaptation,
CVPR18(3801-3809)
IEEE DOI 1812
Training, Collaboration, Feature extraction, Adaptation models, Visualization, Task analysis, Computer vision BibRef

Liu, Y., Wang, Z., Jin, H., Wassell, I.,
Multi-task Adversarial Network for Disentangled Feature Learning,
CVPR18(3743-3751)
IEEE DOI 1812
Training, Generators, Task analysis, Feature extraction, Image generation, Optimization BibRef

Akhtar, N., Liu, J., Mian, A.,
Defense Against Universal Adversarial Perturbations,
CVPR18(3389-3398)
IEEE DOI 1812
Perturbation methods, Training, Computational modeling, Detectors, Neural networks, Robustness, Integrated circuits BibRef

Cao, Z., Long, M., Wang, J., Jordan, M.I.,
Partial Transfer Learning with Selective Adversarial Networks,
CVPR18(2724-2732)
IEEE DOI 1812
Feature extraction, Task analysis, Standards, Big Data, Bridges, Training, Labeling BibRef

Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., Alahi, A.,
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks,
CVPR18(2255-2264)
IEEE DOI 1812
Trajectory, Computational modeling, Predictive models, Generators, History, Decoding BibRef

Zhang, X., Wei, Y., Feng, J., Yang, Y., Huang, T.,
Adversarial Complementary Learning for Weakly Supervised Object Localization,
CVPR18(1325-1334)
IEEE DOI 1812
Training, Feature extraction, Head, Legged locomotion, Task analysis, Pattern recognition, Object recognition BibRef

Zhang, Z., Xie, Y., Yang, L.,
Photographic Text-to-Image Synthesis with a Hierarchically-Nested Adversarial Network,
CVPR18(6199-6208)
IEEE DOI 1812
Generators, Training, Image resolution, Task analysis, Semantics, Measurement BibRef

Chou, Y., Chen, C., Liu, K., Chen, C.,
Stingray Detection of Aerial Images Using Augmented Training Images Generated by a Conditional Generative Model,
Environmental18(1484-14846)
IEEE DOI 1812
Training, Object detection, Generators, Sea surface, Generative adversarial networks, Detectors BibRef

Behpour, S., Xing, W., Ziebart, B.D.,
ARC: Adversarial Robust Cuts for Semi-Supervised and Multi-label Classification,
WiCV18(1986-19862)
IEEE DOI 1812
Markov random fields, Task analysis, Training, Testing, Support vector machines, Fasteners, Games BibRef

Li, R., Cao, W., Qian, S., Wong, H., Wu, S.,
Cross-domain Semantic Feature Learning via Adversarial Adaptation Networks,
ICPR18(37-42)
IEEE DOI 1812
Feature extraction, Semantics, Task analysis, Adaptation models, Data mining, Computational modeling, Generators, adversarial learning BibRef

Hayes, J.,
On Visible Adversarial Perturbations & Digital Watermarking,
PRIV18(1678-16787)
IEEE DOI 1812
Perturbation methods, Watermarking, Computational modeling, Visualization, Task analysis, Image restoration, Computer vision BibRef

Dong, Y., Liao, F., Pang, T., Su, H., Zhu, J., Hu, X., Li, J.,
Boosting Adversarial Attacks with Momentum,
CVPR18(9185-9193)
IEEE DOI 1812
Iterative methods, Robustness, Training, Data models, Adaptation models, Security BibRef

Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., Prakash, A., Kohno, T., Song, D.,
Robust Physical-World Attacks on Deep Learning Visual Classification,
CVPR18(1625-1634)
IEEE DOI 1812
Perturbation methods, Roads, Cameras, Visualization, Pipelines, Autonomous vehicles, Detectors BibRef

Liao, F., Liang, M., Dong, Y., Pang, T., Hu, X., Zhu, J.,
Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser,
CVPR18(1778-1787)
IEEE DOI 1812
Training, Perturbation methods, Noise reduction, Image reconstruction, Predictive models, Neural networks, Adaptation models BibRef

Dolhansky, B., Ferrer, C.C.,
Eye In-painting with Exemplar Generative Adversarial Networks,
CVPR18(7902-7911)
IEEE DOI 1812
Face, Generators, Training, Generative adversarial networks, Task analysis, Painting BibRef

Hong, W.X.[Wei-Xiang], Wang, Z.Z.[Zhen-Zhen], Yang, M.[Ming], Yuan, J.S.[Jun-Song],
Conditional Generative Adversarial Network for Structured Domain Adaptation,
CVPR18(1335-1344)
IEEE DOI 1812
Semantics, Image segmentation, Generators, Training, Adaptation models, Neural networks, Gallium nitride BibRef

Chen, Q.C.[Qing-Chao], Liu, Y.[Yang], Wang, Z.W.[Zhao-Wen], Wassell, I.[Ian], Chetty, K.[Kevin],
Re-weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation,
CVPR18(7976-7985)
IEEE DOI 1812
Feature extraction, Training, Task analysis, Adaptation models, Computer vision, Neural networks, Loss measurement BibRef

Mattyus, G., Urtasun, R.,
Matching Adversarial Networks,
CVPR18(8024-8032)
IEEE DOI 1812
Generators, Training, Task analysis, Perturbation methods, Generative adversarial networks, Image segmentation BibRef

Sankaranarayanan, S., Balaji, Y., Castillo, C.D., Chellappa, R.,
Generate to Adapt: Aligning Domains Using Generative Adversarial Networks,
CVPR18(8503-8512)
IEEE DOI 1812
Generators, Training, Adaptation models, Image generation, Data models, Task analysis BibRef

Gong, Y., Karanam, S., Wu, Z., Peng, K., Ernst, J., Doerschuk, P.C.,
Learning Compositional Visual Concepts with Mutual Consistency,
CVPR18(8659-8668)
IEEE DOI 1812
Training data, Training, Image generation, Generative adversarial networks, Face, Semantics. BibRef

Gao, R., Lu, Y., Zhou, J., Zhu, S., Wu, Y.N.,
Learning Generative ConvNets via Multi-grid Modeling and Sampling,
CVPR18(9155-9164)
IEEE DOI 1812
Training, Monte Carlo methods, Data models, Maximum likelihood estimation, Energy resolution, Probabilistic logic BibRef

Zhang, Z., Yang, L., Zheng, Y.,
Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network,
CVPR18(9242-9251)
IEEE DOI 1812
Image segmentation, Generators, Biomedical imaging, Task analysis, Computed tomography, Training BibRef

Chavdarova, T., Fleuret, F.,
SGAN: An Alternative Training of Generative Adversarial Networks,
CVPR18(9407-9415)
IEEE DOI 1812
Computer vision, Pattern recognition BibRef

Chen, W., Hays, J.,
SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis,
CVPR18(9416-9425)
IEEE DOI 1812
Image edge detection, Image generation, Training, Databases, Task analysis, Generative adversarial networks BibRef

Lin, C., Yumer, E., Wang, O., Shechtman, E., Lucey, S.,
ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing,
CVPR18(9455-9464)
IEEE DOI 1812
Training, Generators, Image generation, Manifolds, Generative adversarial networks, Games BibRef

Chen, Y., Lai, Y., Liu, Y.,
CartoonGAN: Generative Adversarial Networks for Photo Cartoonization,
CVPR18(9465-9474)
IEEE DOI 1812
Training, Generative adversarial networks, Manifolds, Image edge detection, Automobiles, Training data BibRef

Yuan, Y., Liu, S., Zhang, J., Zhang, Y., Dong, C., Lin, L.,
Unsupervised Image Super-Resolution Using Cycle-in-Cycle Generative Adversarial Networks,
Restoration18(814-81409)
IEEE DOI 1812
Image resolution, Kernel, Training, Generators, Degradation, Unsupervised learning BibRef

Barsoum, E., Kender, J., Liu, Z.,
HP-GAN: Probabilistic 3D Human Motion Prediction via GAN,
Joint18(1499-149909)
IEEE DOI 1812
Predictive models, Generative adversarial networks, Probabilistic logic, Generators, Prediction algorithms BibRef

Liu, Y., Guo, Y., Chen, W., Lew, M.S.,
An Extensive Study of Cycle-Consistent Generative Networks for Image-to-Image Translation,
ICPR18(219-224)
IEEE DOI 1812
Generators, Task analysis, Image reconstruction, Generative adversarial networks, Stacking, Bridges BibRef

Li, D., Zhang, M., Chen, W., Feng, G.,
Facial Attribute Editing by Latent Space Adversarial Variational Autoencoders,
ICPR18(1337-1342)
IEEE DOI 1812
Training, Decoding, Image reconstruction, Face, Facial features, Generative adversarial networks BibRef

Ma, R., Hu, H.,
Perceptual Face Completion using a Local-Global Generative Adversarial Network,
ICPR18(1670-1675)
IEEE DOI 1812
Face, Image reconstruction, Training, Feature extraction, Semantics, Task analysis, Generative adversarial networks, completion, perceptual network BibRef

Mopuri, K.R., Ojha, U., Garg, U., Babu, R.V.,
NAG: Network for Adversary Generation,
CVPR18(742-751)
IEEE DOI 1812
Perturbation methods, Generators, Generative adversarial networks, Training, Machine learning, Neural networks BibRef

Hu, L., Kan, M., Shan, S., Chen, X.,
Duplex Generative Adversarial Network for Unsupervised Domain Adaptation,
CVPR18(1498-1507)
IEEE DOI 1812
Generators, Generative adversarial networks, Measurement, Feature extraction, Testing, Object recognition BibRef

Qi, G., Zhang, L., Hu, H., Edraki, M., Wang, J., Hua, X.,
Global Versus Localized Generative Adversarial Nets,
CVPR18(1517-1525)
IEEE DOI 1812
Manifolds, Generators, Geometry, Training, Data models, Semisupervised learning BibRef

Tulyakov, S., Liu, M., Yang, X., Kautz, J.,
MoCoGAN: Decomposing Motion and Content for Video Generation,
CVPR18(1526-1535)
IEEE DOI 1812
Generators, Training, Image generation, Trajectory, Generative adversarial networks, Visualization BibRef

Pal, A., Balasubramanian, V.N.,
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data,
CVPR18(1556-1565)
IEEE DOI 1812
Labeling, Data models, Generative adversarial networks, Computational modeling, Programming BibRef

Xiong, W., Luo, W., Ma, L., Liu, W., Luo, J.,
Learning to Generate Time-Lapse Videos Using Multi-stage Dynamic Generative Adversarial Networks,
CVPR18(2364-2373)
IEEE DOI 1812
Videos, Generative adversarial networks, Generators, Dynamics, Convolution BibRef

Regmi, K., Borji, A.,
Cross-View Image Synthesis Using Conditional GANs,
CVPR18(3501-3510)
IEEE DOI 1812
Image segmentation, Task analysis, Generators, Generative adversarial networks, Image generation, Semantics BibRef

Chen, Y., Lin, H., Shu, M., Li, R., Tao, X., Shen, X., Ye, Y., Jia, J.,
Facelet-Bank for Fast Portrait Manipulation,
CVPR18(3541-3549)
IEEE DOI 1812
Face, Training, Interpolation, Decoding, Generative adversarial networks, Semantics, Transforms BibRef

Lee, K., Xu, W., Fan, F., Tu, Z.,
Wasserstein Introspective Neural Networks,
CVPR18(3702-3711)
IEEE DOI 1812
Generative adversarial networks, Training, Generators, Computational modeling, Convolutional neural networks BibRef

Poursaeed, O., Katsman, I., Gao, B., Belongie, S.,
Generative Adversarial Perturbations,
CVPR18(4422-4431)
IEEE DOI 1812
Perturbation methods, Generators, Task analysis, Semantics, Image segmentation, Iterative methods, Training BibRef

Volpi, R., Morerio, P., Savarese, S., Murino, V.,
Adversarial Feature Augmentation for Unsupervised Domain Adaptation,
CVPR18(5495-5504)
IEEE DOI 1812
Feature extraction, Training, Games, Generative adversarial networks, Generators, Neural networks BibRef

Ma, S., Fu, J., Chen, C.W., Mei, T.,
DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks,
CVPR18(5657-5666)
IEEE DOI 1812
Task analysis, Semantics, Generative adversarial networks, Birds, Geometry BibRef

Shen, Y., Ji, R., Zhang, S., Zuo, W., Wang, Y.,
Generative Adversarial Learning Towards Fast Weakly Supervised Detection,
CVPR18(5764-5773)
IEEE DOI 1812
Detectors, Proposals, Generators, Training, Pipelines, Generative adversarial networks BibRef

Hosseini, H., Poovendran, R.,
Semantic Adversarial Examples,
PRIV18(1695-16955)
IEEE DOI 1812
Image color analysis, Perturbation methods, Semantics, Shape, Security, Automobiles, Marine vehicles BibRef

Wang, T., Liu, M., Zhu, J., Tao, A., Kautz, J., Catanzaro, B.,
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs,
CVPR18(8798-8807)
IEEE DOI 1812
Generators, Image resolution, Semantics, Training, Image generation, Task analysis BibRef

Ghosh, A., Kulharia, V., Namboodiri, V., Torr, P.H.S., Dokania, P.K.,
Multi-agent Diverse Generative Adversarial Networks,
CVPR18(8513-8521)
IEEE DOI 1812
Generators, Task analysis, Training, Generative adversarial networks, Computer architecture, Face BibRef

Dizaji, K.G., Zheng, F., Nourabadi, N.S., Yang, Y., Deng, C., Huang, H.,
Unsupervised Deep Generative Adversarial Hashing Network,
CVPR18(3664-3673)
IEEE DOI 1812
Generators, Training, Task analysis, Generative adversarial networks, Binary codes BibRef

Cao, Y., Liu, B., Long, M., Wang, J.,
HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN,
CVPR18(1287-1296)
IEEE DOI 1812
Generators, Quantization (signal), Training, Training data, Generative adversarial networks BibRef

Ouyang, X., Zhang, X., Ma, D., Agam, G.,
Generating Image Sequence from Description with LSTM Conditional GAN,
ICPR18(2456-2461)
IEEE DOI 1812
Generators, Semantics, Image generation, Training, Logic gates, Neural networks BibRef

Zhang, C., Feng, Y., Qiang, B., Shang, J.,
Wasserstein Generative Recurrent Adversarial Networks for Image Generating,
ICPR18(242-247)
IEEE DOI 1812
Generators, Generative adversarial networks, Training, Mathematical model, Earth, Image generation, recurrent nerual netwoks BibRef

Fang, Y., Yuan, Q., Zhang, W., Zhang, Z.,
Diversified Dual Domain-Adversarial Neural Networks,
ICPR18(615-620)
IEEE DOI 1812
Feature extraction, Adaptation models, Training, Task analysis, Neural networks, Data models BibRef

Yu, P., Song, K., Lu, J.,
Generating Adversarial Examples With Conditional Generative Adversarial Net,
ICPR18(676-681)
IEEE DOI 1812
Training, Perturbation methods, Generators, Data models, Generative adversarial networks, Computational modeling, BibRef

Sun, D., Zhang, Q., Yang, J.,
Pyramid Embedded Generative Adversarial Network for Automated Font Generation,
ICPR18(976-981)
IEEE DOI 1812
Generators, Decoding, Generative adversarial networks, Training, Task analysis, Image generation BibRef

Liu, X., Meng, G., Xiang, S., Pan, C.,
Semantic Image Synthesis via Conditional Cycle-Generative Adversarial Networks,
ICPR18(988-993)
IEEE DOI 1812
Birds, Generators, Generative adversarial networks, Semantics, Training, Image generation BibRef

Wu, K., Zhang, C.,
Deep Generative Adversarial Networks for the Sparse Signal Denoising,
ICPR18(1127-1132)
IEEE DOI 1812
Noise reduction, Encoding, Task analysis, Data models, Generative adversarial networks BibRef

Karim, R., Islam, M.A., Mohammed, N., Bruce, N.D.B.,
On the Robustness of Deep Learning Models to Universal Adversarial Attack,
CRV18(55-62)
IEEE DOI 1812
Perturbation methods, Computational modeling, Neural networks, Task analysis, Image segmentation, Data models, Semantics, Semantic Segmentation BibRef

Guo, Y.[Ye], Liu, K.[Ke], Yu, Z.Y.[Ze-Yun],
Porous Structure Design in Tissue Engineering Using Anisotropic Radial Basis Functions,
ISVC18(79-90).
Springer DOI 1811
BibRef

Makkapati, V.V.[Vishnu Vardhan], Patro, A., (2017)
Enhancing Symmetry in GAN Generated Fashion Images,
SGAI17(xx-yy).
Springer DOI LNCS 10630. 1811
BibRef

Patro, A., Makkapati, V.V.[Vishnu Vardhan], Mukhopadhyay, J.,
Evaluation of Loss Functions for Estimation of Latent Vectors from GAN,
MLSP18(1-6).
IEEE DOI 1811
BibRef

Tran, N.T.[Ngoc-Trung], Bui, T.A.[Tuan-Anh], Cheung, N.M.[Ngai-Man],
Dist-GAN: An Improved GAN Using Distance Constraints,
ECCV18(XIV: 387-401).
Springer DOI 1810
BibRef

Zhao, B.[Bo], Chang, B.[Bo], Jie, Z.[Zequn], Sigal, L.[Leonid],
Modular Generative Adversarial Networks,
ECCV18(XIV: 157-173).
Springer DOI 1810
BibRef

Zhou, W.[Wen], Hou, X.[Xin], Chen, Y.J.[Yong-Jun], Tang, M.Y.[Meng-Yun], Huang, X.Q.[Xiang-Qi], Gan, X.[Xiang], Yang, Y.[Yong],
Transferable Adversarial Perturbations,
ECCV18(XIV: 471-486).
Springer DOI 1810
BibRef

Jha, A.H.[Ananya Harsh], Anand, S.[Saket], Singh, M.[Maneesh], Veeravasarapu, V.S.R.,
Disentangling Factors of Variation with Cycle-Consistent Variational Auto-encoders,
ECCV18(III: 829-845).
Springer DOI 1810
BibRef

Edraki, M.[Marzieh], Qi, G.J.[Guo-Jun],
Generalized Loss-Sensitive Adversarial Learning with Manifold Margins,
ECCV18(VI: 90-104).
Springer DOI 1810
BibRef

Vivek, B.S., Mopuri, K.R.[Konda Reddy], Babu, R.V.[R. Venkatesh],
Gray-Box Adversarial Training,
ECCV18(XV: 213-228).
Springer DOI 1810
BibRef

Wang, J.[Jue], Cherian, A.[Anoop], Porikli, F.M.[Fatih M.], Gould, S.,
Video Representation Learning Using Discriminative Pooling,
CVPR18(1149-1158)
IEEE DOI 1812
Support vector machines, Computational modeling, Task analysis, Feature extraction, Computer vision, Data models, Kernel BibRef

Wang, J.[Jue], Cherian, A.[Anoop],
Learning Discriminative Video Representations Using Adversarial Perturbations,
ECCV18(II: 716-733).
Springer DOI 1810
BibRef

Chang, C.C.[Chia-Che], Lin, C.H.[Chieh Hubert], Lee, C.R.[Che-Rung], Juan, D.C.[Da-Cheng], Wei, W.[Wei], Chen, H.T.[Hwann-Tzong],
Escaping from Collapsing Modes in a Constrained Space,
ECCV18(VII: 212-227).
Springer DOI 1810
mode collapse issue in GANs BibRef

Chen, X.Y.[Xin-Yuan], Xu, C.[Chang], Yang, X.K.[Xiao-Kang], Tao, D.C.[Da-Cheng],
Attention-GAN for Object Transfiguration in Wild Images,
ECCV18(II: 167-184).
Springer DOI 1810
BibRef

Shmelkov, K.[Konstantin], Schmid, C.[Cordelia], Alahari, K.[Karteek],
How Good Is My GAN?,
ECCV18(II: 218-234).
Springer DOI 1810
BibRef

Liang, X.D.[Xiao-Dan], Zhang, H.[Hao], Lin, L.[Liang], Xing, E.[Eric],
Generative Semantic Manipulation with Mask-Contrasting GAN,
ECCV18(XIII: 574-590).
Springer DOI 1810
BibRef

He, Y.[Yang], Schiele, B.[Bernt], Fritz, M.[Mario],
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes,
ECCV18(XVI: 422-437).
Springer DOI 1810
BibRef

Wang, Y.X.[Ya-Xing], Wu, C.S.[Chen-Shen], Herranz, L.[Luis], van de Weijer, J.[Joost], Gonzalez-Garcia, A.[Abel], Raducanu, B.[Bogdan],
Transferring GANs: Generating Images from Limited Data,
ECCV18(VI: 220-236).
Springer DOI 1810
BibRef

Wu, J.Q.[Ji-Qing], Huang, Z.W.[Zhi-Wu], Thoma, J.[Janine], Acharya, D.[Dinesh], Van Gool, L.J.[Luc J.],
Wasserstein Divergence for GANs,
ECCV18(VI: 673-688).
Springer DOI 1810
BibRef

Bodla, N.[Navaneeth], Hua, G.[Gang], Chellappa, R.[Rama],
Semi-supervised FusedGAN for Conditional Image Generation,
ECCV18(VI: 689-704).
Springer DOI 1810
BibRef

Ge, H.[Hao], Xia, Y.[Yin], Chen, X.[Xu], Berry, R.[Randall], Wu, Y.[Ying],
Fictitious GAN: Training GANs with Historical Models,
ECCV18(I: 122-137).
Springer DOI 1810
BibRef

Jakubovitz, D.[Daniel], Giryes, R.[Raja],
Improving DNN Robustness to Adversarial Attacks Using Jacobian Regularization,
ECCV18(XII: 525-541).
Springer DOI 1810
BibRef

Gecer, B.[Baris], Bhattarai, B.[Binod], Kittler, J.V.[Josef V.], Kim, T.K.[Tae-Kyun],
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model,
ECCV18(XI: 230-248).
Springer DOI 1810
BibRef

Kang, G.L.[Guo-Liang], Zheng, L.[Liang], Yan, Y.[Yan], Yang, Y.[Yi],
Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: The Benefit of Target Expectation Maximization,
ECCV18(XI: 420-436).
Springer DOI 1810
BibRef

Felsen, P.[Panna], Lucey, P.[Patrick], Ganguly, S.[Sujoy],
Where Will They Go? Predicting Fine-Grained Adversarial Multi-agent Motion Using Conditional Variational Autoencoders,
ECCV18(XI: 761-776).
Springer DOI 1810
BibRef

Xu, K.[Kai], Zhang, Z.[Zhikang], Ren, F.[Fengbo],
LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction,
ECCV18(X: 491-507).
Springer DOI 1810
BibRef

Li, M.J.[Min-Jun], Huang, H.Z.[Hao-Zhi], Ma, L.[Lin], Liu, W.[Wei], Zhang, T.[Tong], Jiang, Y.G.[Yu-Gang],
Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks,
ECCV18(IX: 186-201).
Springer DOI 1810
BibRef

Wang, C.[Chao], Zheng, H.[Haiyong], Yu, Z.B.[Zhi-Bin], Zheng, Z.Q.[Zi-Qiang], Gu, Z.[Zhaorui], Zheng, B.[Bing],
Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation,
ECCV18(I: 796-812).
Springer DOI 1810
BibRef

Li, Y.[Ya], Tian, X.[Xinmei], Gong, M.M.[Ming-Ming], Liu, Y.J.[Ya-Jing], Liu, T.L.[Tong-Liang], Zhang, K.[Kun], Tao, D.C.[Da-Cheng],
Deep Domain Generalization via Conditional Invariant Adversarial Networks,
ECCV18(XV: 647-663).
Springer DOI 1810
BibRef

Zhang, X.[Xi], Lai, H.J.[Han-Jiang], Feng, J.S.[Jia-Shi],
Attention-Aware Deep Adversarial Hashing for Cross-Modal Retrieval,
ECCV18(XV: 614-629).
Springer DOI 1810
BibRef

Lu, Y.Y.[Yong-Yi], Wu, S.Z.[Shang-Zhe], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
Image Generation from Sketch Constraint Using Contextual GAN,
ECCV18(XVI: 213-228).
Springer DOI 1810
BibRef

Liang, J.[Jie], Yang, J.F.[Ju-Feng], Lee, H.Y.[Hsin-Ying], Wang, K.[Kai], Yang, M.H.[Ming-Hsuan],
Sub-GAN: An Unsupervised Generative Model via Subspaces,
ECCV18(XI: 726-743).
Springer DOI 1810
BibRef

Wang, G.[Guan'an], Hu, Q.[Qinghao], Cheng, J.[Jian], Hou, Z.G.[Zeng-Guang],
Semi-supervised Generative Adversarial Hashing for Image Retrieval,
ECCV18(XV: 491-507).
Springer DOI 1810
BibRef

Wu, Z.Y.[Zhen-Yu], Wang, Z.Y.[Zhang-Yang], Wang, Z.W.[Zhao-Wen], Jin, H.L.[Hai-Lin],
Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study,
ECCV18(XVI: 627-645).
Springer DOI
WWW Link. 1810
See also Privacy-Preserving Visual Recognition PA-HMDB51. BibRef

Sah, S.[Shagan], Shringi, A.[Ameya], Peri, D.[Dheeraj], Hamilton, J.[John], Savakis, A.[Andreas], Ptucha, R.[Ray],
Multimodal Reconstruction Using Vector Representation,
ICIP18(3763-3767)
IEEE DOI 1809
Image reconstruction, Training, Decoding, Visualization, Image generation, Task analysis, Correlation BibRef

Halici, E., Alatan, A.A.[A. Aydin],
Object Localization Without Bounding Box Information Using Generative Adversarial Reinforcement Learning,
ICIP18(3728-3732)
IEEE DOI 1809
Agriculture, Learning (artificial intelligence), Automobiles, Training, Image databases, Measurement, Object Localization, Generative Adversarial Reinforcement Learning BibRef

Chiaroni, F., Rahal, M., Hueber, N., Dufaux, F.,
Learning with A Generative Adversarial Network From a Positive Unlabeled Dataset for Image Classification,
ICIP18(1368-1372)
IEEE DOI 1809
Training, Generative adversarial networks, Learning systems, Computational modeling, Kernel, Neurons, Generative Models BibRef

Ravanbakhsh, M., Baydoun, M., Campo, D., Marin, P., Martin, D., Marcenaro, L., Regazzoni, C.S.,
Hierarchy of GANs for Learning Embodied Self-Awareness Model,
ICIP18(1987-1991)
IEEE DOI 1809
Data models, Optical imaging, Training, Task analysis, Generative adversarial networks, Anomaly detection BibRef

Jin, G., Zhang, D., Dai, F., Guo, J., Ma, Y., Zhang, Y.,
Semantic Preserving Hash Coding Through VAE-GAN,
ICIP18(1997-2001)
IEEE DOI 1809
Semantics, Generators, Machine learning, Training, Binary codes, Image generation, Image retrieval, Generative adversarial network BibRef

Li, C., Wang, Z., Qi, H.,
Fast-Converging Conditional Generative Adversarial Networks for Image Synthesis,
ICIP18(2132-2136)
IEEE DOI 1809
Generators, Generative adversarial networks, Convergence, Image generation, Visualization, Training, image synthesis BibRef

Kosmopoulos, D.I.,
A Prototype Towards Modeling Visual Data Using Decentralized Generative Adversarial Networks,
ICIP18(4163-4167)
IEEE DOI 1809
Training, Generative adversarial networks, Optimization, Generators, Data models, Games, decentralized learning, BibRef

Cheung, S.S.[S. Samson], Wildfeuer, H., Nikkhah, M., Zhu, X., Tan, W.,
Learning Sensitive Images Using Generative Models,
ICIP18(4128-4132)
IEEE DOI 1809
Training, Face, Generative adversarial networks, Privacy, Data privacy, Machine learning, face processing BibRef

Rukhkhattak, G., Vallecorsa, S., Carminati, F.,
Three Dimensional Energy Parametrized Generative Adversarial Networks for Electromagnetic Shower Simulation,
ICIP18(3913-3917)
IEEE DOI 1809
Generative adversarial networks, Detectors, Generators, Physics, Training, Monte Carlo methods, HEP, Simulation, GAN BibRef

Kancharla, P., Channappayya, S.S.,
Improving the Visual Quality of Generative Adversarial Network (GAN)-Generated Images Using the Multi-Scale Structural Similarity Index,
ICIP18(3908-3912)
IEEE DOI 1809
Generative adversarial networks, Visualization, Indexes, Standards, Image quality, Training, Natural Scene Statistics BibRef

Zhang, Z., Sun, Y., Yu, J.,
A Cross-Layer Based Network for Faster Image Generation,
ICIP18(3903-3907)
IEEE DOI 1809
Generators, Training, Computer architecture, Image generation, Face, Generative adversarial networks, cross-layer connection BibRef

Rozsa, A., Gunther, M., Boult, T.E.,
Towards Robust Deep Neural Networks with BANG,
WACV18(803-811)
IEEE DOI 1806
image processing, learning (artificial intelligence), neural nets, BANG technique, adversarial image utilization, Training BibRef

Gammulle, H.[Harshala], Fernando, T.[Tharindu], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Coupled Generative Adversarial Network for Continuous Fine-Grained Action Segmentation,
WACV19(200-209)
IEEE DOI 1904
BibRef
Earlier: A2, A3, A4, A5, Only:
Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks,
WACV18(1539-1548)
IEEE DOI 1806
feature extraction, image recognition, image representation, image segmentation, image sequences, Couplings. image classification, image representation, learning (artificial intelligence), Visualization. BibRef

Peleg, I., Wolf, L.B.[Lior B.],
Structured GANs,
WACV18(719-728)
IEEE DOI 1806
image processing, learning (artificial intelligence), neural nets, face image synthesis, Training BibRef

Chai, W., Deng, W., Shen, H.,
Cross-Generating GAN for Facial Identity Preserving,
FG18(130-134)
IEEE DOI 1806
Encoding, Face, Face recognition, Feature extraction, Finite impulse response filters, Lighting, CG GAN, Multi PIE BibRef

Liu, Y., Wang, Q., Gu, Y., Kamijo, S.,
A Latent Space Understandable Generative Adversarial Network: SelfExGAN,
DICTA17(1-8)
IEEE DOI 1804
game theory, unsupervised learning, Self- ExGAN, adversarial learning, Training data BibRef

Yi, Z.[Zili], Zhang, H.[Hao], Tan, P.[Ping], Gong, M.L.[Ming-Lun],
DualGAN: Unsupervised Dual Learning for Image-to-Image Translation,
ICCV17(2868-2876)
IEEE DOI 1802
computational complexity, image reconstruction, unsupervised learning. BibRef

Mao, X., Li, Q., Xie, H., Lau, R.Y.K., Wang, Z., Smolley, S.P.,
Least Squares Generative Adversarial Networks,
ICCV17(2813-2821)
IEEE DOI 1802
image classification, least squares approximations, unsupervised learning, LSGANs, Stability analysis BibRef

Palazzo, S., Spampinato, C., Kavasidis, I., Giordano, D., Shah, M.,
Generative Adversarial Networks Conditioned by Brain Signals,
ICCV17(3430-3438)
IEEE DOI 1802
brain, electroencephalography, image representation, learning (artificial intelligence), medical image processing, Visualization BibRef

Tung, H.Y.F., Harley, A.W., Seto, W., Fragkiadaki, K.,
Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision,
ICCV17(4364-4372)
IEEE DOI 1802
face recognition, image matching, image resolution, learning (artificial intelligence), motion estimation, BibRef

Li, X., Li, F.,
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics,
ICCV17(5775-5783)
IEEE DOI 1802
convolution, image classification, image filtering, learning (artificial intelligence), neural nets, Training BibRef

Alvarez-Gila, A., van de Weijer, J.[Joost], Garrote, E.,
Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB,
PBVDL17(480-490)
IEEE DOI 1802
Generators, Hyperspectral imaging, Image reconstruction, Imaging, Semantics BibRef

Di, X., Yu, P.,
Max-Boost-GAN: Max Operation to Boost Generative Ability of Generative Adversarial Networks,
CEFR-LCV17(1156-1164)
IEEE DOI 1802
Convergence, Gallium nitride, Generators, Semantics, Training, Training data, Visualization BibRef

Di, X., Yu, P.,
Multiplicative Noise Channel in Generative Adversarial Networks,
CEFR-LCV17(1165-1172)
IEEE DOI 1802
Additive noise, Additives, Convergence, Gallium nitride, Gaussian noise, Uncertainty, Visualization BibRef

Choe, J., Park, S., Kim, K., Park, J.H., Kim, D., Shim, H.,
Face Generation for Low-Shot Learning Using Generative Adversarial Networks,
Million17(1940-1948)
IEEE DOI 1802
Face, Face recognition, Feature extraction, Gallium nitride, Generators, Image reconstruction, Training BibRef

Giuffrida, M.V., Scharr, H., Tsaftaris, S.A.,
ARIGAN: Synthetic Arabidopsis Plants Using Generative Adversarial Network,
CVPPP17(2064-2071)
IEEE DOI 1802
Computational modeling, Data models, Gallium nitride, Generators, Neural networks, Training BibRef

Mukuta, Y., Ushiku, Y., Harada, T.,
Spatial-Temporal Weighted Pyramid Using Spatial Orthogonal Pooling,
CEFR-LCV17(1041-1049)
IEEE DOI 1802
Encoding, Feature extraction, Robustness, Spatial resolution, Standards BibRef

Harada, T., Saito, K., Mukuta, Y., Ushiku, Y.,
Deep Modality Invariant Adversarial Network for Shared Representation Learning,
TASKCV17(2623-2629)
IEEE DOI 1802
Feature extraction, Games, Gaussian distribution, Generators, Training, Videos BibRef

Metzen, J.H.[Jan Hendrik], Kumar, M.C.[Mummadi Chaithanya], Brox, T.[Thomas], Fischer, V.[Volker],
Universal Adversarial Perturbations Against Semantic Image Segmentation,
ICCV17(2774-2783)
IEEE DOI 1802
Noise specifically generated to fool the system. image denoising, image segmentation, learning (artificial intelligence), arbitrary inputs, BibRef

Moosavi-Dezfooli, S.M.[Seyed-Mohsen], Fawzi, A.[Alhussein], Fawzi, O.[Omar], Frossard, P.[Pascal],
Universal Adversarial Perturbations,
CVPR17(86-94)
IEEE DOI 1711
Computer architecture, Correlation, Neural networks, Optimization, Robustness, Training, Visualization BibRef

Narodytska, N., Kasiviswanathan, S.,
Simple Black-Box Adversarial Attacks on Deep Neural Networks,
PRIV17(1310-1318)
IEEE DOI 1709
Computer vision, Knowledge engineering, Network architecture, Neural networks, Robustness, Training BibRef

Wang, X., Shrivastava, A., Gupta, A.,
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection,
CVPR17(3039-3048)
IEEE DOI 1711
Detectors, Feature extraction, Object detection, Proposals, Strain, Training BibRef

Huang, X.[Xun], Li, Y.X.[Yi-Xuan], Poursaeed, O.[Omid], Hopcroft, J.[John], Belongie, S.J.[Serge J.],
Stacked Generative Adversarial Networks,
CVPR17(1866-1875)
IEEE DOI 1711
Data models, Entropy, Generators, Image reconstruction, Training BibRef

Saito, M., Matsumoto, E., Saito, S.,
Temporal Generative Adversarial Nets with Singular Value Clipping,
ICCV17(2849-2858)
IEEE DOI 1802
Bayes methods, deconvolution, learning (artificial intelligence), unsupervised learning, video signal processing, generative model, Videos BibRef

Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., Krishnan, D.,
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks,
CVPR17(95-104)
IEEE DOI 1711
Adaptation models, Feature extraction, Gallium nitride, Generators, Google, Training BibRef

Lu, J., Issaranon, T., Forsyth, D.A.,
SafetyNet: Detecting and Rejecting Adversarial Examples Robustly,
ICCV17(446-454)
IEEE DOI 1802
image colour analysis, image reconstruction, learning (artificial intelligence), neural nets, BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Bayesian Learning, Bayes Network, Bayesian Networks .


Last update:Aug 20, 2019 at 20:38:45