Li, W.[Wen],
Xu, Z.[Zheng],
Xu, D.[Dong],
Dai, D.X.[Deng-Xin],
Van Gool, L.J.[Luc J.],
Domain Generalization and Adaptation Using Low Rank Exemplar SVMs,
PAMI(40), No. 5, May 2018, pp. 1114-1127.
IEEE DOI
1804
Linear programming, Logistics, Support vector machines, Testing,
Training, Videos, Visualization, Latent domains, domain adaptation,
exemplar SVMs
BibRef
Wang, Y.,
Li, W.,
Dai, D.X.[Deng-Xin],
Van Gool, L.J.[Luc J.],
Deep Domain Adaptation by Geodesic Distance Minimization,
TASKCV17(2651-2657)
IEEE DOI
1802
Adaptation models, Covariance matrices, Euclidean distance,
Feature extraction, Manifolds, Training data, Visualization
BibRef
Lee, W.[Woojin],
Kim, H.[Hoki],
Lee, J.W.[Jae-Wook],
Compact class-conditional domain invariant learning for multi-class
domain adaptation,
PR(112), 2021, pp. 107763.
Elsevier DOI
2102
Domain adaptation, Generalization bound,
Class-conditional domain invariant learning, Transfer Learning
BibRef
Li, H.L.[Hao-Liang],
Wang, S.Q.[Shi-Qi],
Wan, R.J.[Ren-Jie],
Kot, A.C.[Alex C.],
GMFAD: Towards Generalized Visual Recognition via Multilayer Feature
Alignment and Disentanglement,
PAMI(44), No. 3, March 2022, pp. 1289-1303.
IEEE DOI
2202
Adaptation models, Machine learning, Training, Task analysis,
Data models, Correlation, Training data, Generalization capability,
visual recognition
BibRef
Wang, H.[Hao],
Bi, X.J.[Xiao-Jun],
Domain generalization and adaptation based on second-order style
information,
PR(127), 2022, pp. 108595.
Elsevier DOI
2205
Domain generalization, Unsupervised domain adaptation,
Two-level style normalization and restitution,
Dynamic affine parameter
BibRef
Yuan, M.L.[Ming-Lei],
Cai, C.H.[Chun-Hao],
Lu, T.[Tong],
Wu, Y.R.[Yi-Rui],
Xu, Q.[Qian],
Zhou, S.J.[Shi-Jie],
A novel forget-update module for few-shot domain generalization,
PR(129), 2022, pp. 108704.
Elsevier DOI
2206
Few-shot classification, Domain adaptation, Few-shot domain generalization
BibRef
Wang, Y.[Yue],
Qi, L.[Lei],
Shi, Y.[Yinghuan],
Gao, Y.[Yang],
Feature-Based Style Randomization for Domain Generalization,
CirSysVideo(32), No. 8, August 2022, pp. 5495-5509.
IEEE DOI
2208
Training, Data models, Adaptation models, Feature extraction,
Standards, Training data, Task analysis, Domain generalization,
style randomization
BibRef
Ge, Z.Q.[Zhi-Qiang],
Song, Z.H.[Zhi-Huan],
Li, X.[Xin],
Zhang, L.[Lei],
Meta conditional variational auto-encoder for domain generalization,
CVIU(222), 2022, pp. 103503.
Elsevier DOI
2209
Meta learning, Conditional variational, Domain generalization,
Wasserstein distance
BibRef
Christiansen, R.[Rune],
Pfister, N.[Niklas],
Jakobsen, M.E.[Martin Emil],
Gnecco, N.[Nicola],
Peters, J.[Jonas],
A Causal Framework for Distribution Generalization,
PAMI(44), No. 10, October 2022, pp. 6614-6630.
IEEE DOI
2209
Training, Predictive models, Analytical models, Mathematical model,
Training data, Testing, Task analysis, Distribution generalization,
domain adaptation
BibRef
Du, D.P.[Da-Peng],
Chen, J.W.[Jia-Wei],
Li, Y.X.[Yue-Xiang],
Ma, K.[Kai],
Wu, G.S.[Gang-Shan],
Zheng, Y.F.[Ye-Feng],
Wang, L.M.[Li-Min],
Cross-Domain Gated Learning for Domain Generalization,
IJCV(130), No. 11, November 2022, pp. 2842-2857.
Springer DOI
2210
BibRef
Wang, R.Q.[Rui-Qi],
Qi, L.[Lei],
Shi, Y.[Yinghuan],
Gao, Y.[Yang],
Better pseudo-label: Joint domain-aware label and dual-classifier for
semi-supervised domain generalization,
PR(133), 2023, pp. 108987.
Elsevier DOI
2210
Semi-supervised learning, Domain generalization,
Image recognition, Feature representation
BibRef
Chen, S.[Sentao],
Wang, L.[Lei],
Hong, Z.[Zijie],
Yang, X.W.[Xiao-Wei],
Domain Generalization by Joint-Product Distribution Alignment,
PR(134), 2023, pp. 109086.
Elsevier DOI
2212
Distribution alignment, Distribution divergence,
Domain generalization, Feature transformation
BibRef
Saranrittichai, P.[Piyapat],
Mummadi, C.K.[Chaithanya Kumar],
Blaiotta, C.[Claudia],
Munoz, M.[Mauricio],
Fischer, V.[Volker],
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic
Visual Factors from a Source Domain,
ECCV22(XXV:294-309).
Springer DOI
2211
BibRef
Zhang, J.[Jian],
Qi, L.[Lei],
Shi, Y.[Yinghuan],
Gao, Y.[Yang],
MVDG: A Unified Multi-view Framework for Domain Generalization,
ECCV22(XXVII:161-177).
Springer DOI
2211
BibRef
Nam, G.[Gilhyun],
Choi, G.[Gyeongjae],
Lee, K.[Kyungmin],
GCISG: Guided Causal Invariant Learning for Improved Syn-to-Real
Generalization,
ECCV22(XXXIII:656-672).
Springer DOI
2211
BibRef
Zhang, C.[Chi],
Xie, S.[Sirui],
Jia, B.X.[Bao-Xiong],
Wu, Y.N.[Ying Nian],
Zhu, S.C.[Song-Chun],
Zhu, Y.X.[Yi-Xin],
Learning Algebraic Representation for Systematic Generalization in
Abstract Reasoning,
ECCV22(XXIX:692-709).
Springer DOI
2211
BibRef
Fang, F.[Fen],
Liang, W.Y.[Wen-Yu],
Wu, Y.[Yan],
Xu, Q.[Qianli],
Lim, J.H.[Joo-Hwee],
Improving Generalization of Reinforcement Learning Using a Bilinear
Policy Network,
ICIP22(991-995)
IEEE DOI
2211
Representation learning, Visualization, Reinforcement learning,
Object detection, Games, Feature extraction, Path planning, Generalization
BibRef
Xu, W.X.[Wei-Xiang],
Cheng, J.[Jian],
Stacking More Linear Operations with Orthogonal Regularization to
Learn Better,
ICIP22(2731-2735)
IEEE DOI
2211
Training, Deep learning, Runtime, Convolution, Stacking,
Over-parameterization, Model generalization, Orthogonal regularization
BibRef
Meng, R.[Rang],
Li, X.F.[Xian-Feng],
Chen, W.J.[Wei-Jie],
Yang, S.[Shicai],
Song, J.[Jie],
Wang, X.C.[Xin-Chao],
Zhang, L.[Lei],
Song, M.L.[Ming-Li],
Xie, D.[Di],
Pu, S.L.[Shi-Liang],
Attention Diversification for Domain Generalization,
ECCV22(XXXIV:322-340).
Springer DOI
2211
BibRef
Kim, D.H.[Dong-Hyun],
Wang, K.[Kaihong],
Sclaroff, S.[Stan],
Saenko, K.[Kate],
A Broad Study of Pre-training for Domain Generalization and Adaptation,
ECCV22(XXXIII:621-638).
Springer DOI
2211
BibRef
Kulinski, S.[Sean],
Inouye, D.I.[David I.],
Towards Explaining Image-Based Distribution Shifts,
VDU22(4787-4791)
IEEE DOI
2210
Conferences, Pattern recognition, Task analysis
BibRef
Liang, Y.Z.[Yuan-Zhi],
Zhu, L.C.[Lin-Chao],
Wang, X.H.[Xiao-Han],
Yang, Y.[Yi],
A Simple Episodic Linear Probe Improves Visual Recognition in the
Wild,
CVPR22(9549-9559)
IEEE DOI
2210
Training, Visualization, Performance gain, Time measurement,
Probability distribution, Pattern recognition, retrieval
BibRef
Gominski, D.[Dimitri],
Gouet-Brunet, V.[Valérie],
Chen, L.M.[Li-Ming],
Cross-dataset Learning for Generalizable Land Use Scene
Classification,
EarthVision22(1381-1390)
IEEE DOI
2210
Training, Visualization, Image analysis,
Image retrieval, Feature extraction
BibRef
Cugu, I.[Ilke],
Mancini, M.[Massimiliano],
Chen, Y.[Yanbei],
Akata, Z.[Zeynep],
Attention Consistency on Visual Corruptions for Single-Source Domain
Generalization,
L3D-IVU22(4164-4173)
IEEE DOI
2210
Training, Visualization, Training data, Lighting, Benchmark testing,
Picture archiving and communication systems, Data models
BibRef
Lehner, A.[Alexander],
Gasperini, S.[Stefano],
Marcos-Ramiro, A.[Alvaro],
Schmidt, M.[Michael],
Mahani, M.A.N.[Mohammad-Ali Nikouei],
Navab, N.[Nassir],
Busam, B.[Benjamin],
Tombari, F.[Federico],
3D-VField: Adversarial Augmentation of Point Clouds for Domain
Generalization in 3D Object Detection,
CVPR22(17274-17283)
IEEE DOI
2210
Point cloud compression, Training, Shape, Object detection,
Detectors, Automobiles, Navigation and autonomous driving,
Adversarial attack and defense
BibRef
Kim, S.W.[Seung Wook],
Kreis, K.[Karsten],
Li, D.Q.[Dai-Qing],
Torralba, A.[Antonio],
Fidler, S.[Sanja],
Polymorphic-GAN:
Generating Aligned Samples across Multiple Domains with Learned Morph Maps,
CVPR22(10620-10630)
IEEE DOI
2210
Training, Geometry, Image segmentation, Shape,
Generative adversarial networks, Generators,
Transfer/low-shot/long-tail learning
BibRef
Huang, Z.Y.[Ze-Yi],
Wang, H.[Haohan],
Huang, D.[Dong],
Lee, Y.J.[Yong Jae],
Xing, E.P.[Eric P.],
The Two Dimensions of Worst-case Training and Their Integrated Effect
for Out-of-domain Generalization,
CVPR22(9621-9631)
IEEE DOI
2210
Training, Representation learning, Correlation, Merging, Force,
Robustness, Self- semi- meta- Representation learning
BibRef
Bayasi, N.[Nourhan],
Hamarneh, G.[Ghassan],
Garbi, R.[Rafeef],
BoosterNet: Improving Domain Generalization of Deep Neural Nets using
Culpability-Ranked Features,
CVPR22(528-538)
IEEE DOI
2210
Training, Deep learning, Neural networks, Mission critical systems,
Measurement uncertainty, Imaging, Network architecture,
Efficient learning and inferences
BibRef
Wan, C.[Chaoqun],
Shen, X.[Xu],
Zhang, Y.G.[Yong-Gang],
Yin, Z.H.[Zhi-Heng],
Tian, X.[Xinmei],
Gao, F.[Feng],
Huang, J.Q.[Jian-Qiang],
Hua, X.S.[Xian-Sheng],
Meta Convolutional Neural Networks for Single Domain Generalization,
CVPR22(4672-4681)
IEEE DOI
2210
Convolutional codes, Representation learning, Visualization,
Image recognition, Benchmark testing, Image representation,
Deep learning architectures and techniques
BibRef
Zhang, X.X.[Xing-Xuan],
Zhou, L.J.[Lin-Jun],
Xu, R.Z.[Ren-Zhe],
Cui, P.[Peng],
Shen, Z.[Zheyan],
Liu, H.X.[Hao-Xin],
Towards Unsupervised Domain Generalization,
CVPR22(4900-4910)
IEEE DOI
2210
Representation learning, Analytical models, Protocols,
Computational modeling, Data models, Pattern recognition,
Vision applications and systems
BibRef
Harary, S.[Sivan],
Schwartz, E.[Eli],
Arbelle, A.[Assaf],
Staar, P.[Peter],
Abu-Hussein, S.[Shady],
Amrani, E.[Elad],
Herzig, R.[Roei],
Alfassy, A.[Amit],
Giryes, R.[Raja],
Kuehne, H.[Hilde],
Katabi, D.[Dina],
Saenko, K.[Kate],
Feris, R.[Rogerio],
Karlinsky, L.[Leonid],
Unsupervised Domain Generalization by Learning a Bridge Across
Domains,
CVPR22(5270-5280)
IEEE DOI
2210
Bridges, Training, Representation learning, Visualization, Semantics,
Self-supervised learning, Visual systems, Recognition: detection,
Representation learning
BibRef
Zhu, W.[Wei],
Lu, L.[Le],
Xiao, J.[Jing],
Han, M.[Mei],
Luo, J.B.[Jie-Bo],
Harrison, A.P.[Adam P.],
Localized Adversarial Domain Generalization,
CVPR22(7098-7108)
IEEE DOI
2210
Deep learning, Training data, Games, Benchmark testing,
Maintenance engineering, Pattern recognition, Machine learning
BibRef
Chen, C.Q.[Chao-Qi],
Li, J.[Jiongcheng],
Han, X.G.[Xiao-Guang],
Liu, X.Q.[Xiao-Qing],
Yu, Y.Z.[Yi-Zhou],
Compound Domain Generalization via Meta-Knowledge Encoding,
CVPR22(7109-7119)
IEEE DOI
2210
Representation learning, Semantics, Prototypes, Object detection,
Benchmark testing, Encoding, Pattern recognition, Representation learning
BibRef
Kang, J.[Juwon],
Lee, S.[Sohyun],
Kim, N.[Namyup],
Kwak, S.[Suha],
Style Neophile: Constantly Seeking Novel Styles for Domain
Generalization,
CVPR22(7120-7130)
IEEE DOI
2210
Greedy algorithms, Training, Representation learning,
Computational modeling, Training data, Benchmark testing,
retrieval
BibRef
Zhang, H.L.[Han-Lin],
Zhang, Y.F.[Yi-Fan],
Liu, W.Y.[Wei-Yang],
Weller, A.[Adrian],
Schölkopf, B.[Bernhard],
Xing, E.P.[Eric P.],
Towards Principled Disentanglement for Domain Generalization,
CVPR22(8014-8024)
IEEE DOI
2210
Training, Correlation, Semantics, Training data, Machine learning,
Benchmark testing, Transfer/low-shot/long-tail learning,
privacy and ethics in vision
BibRef
Zhang, Y.[Yabin],
Li, M.[Minghan],
Li, R.[Ruihuang],
Jia, K.[Kui],
Zhang, L.[Lei],
Exact Feature Distribution Matching for Arbitrary Style Transfer and
Domain Generalization,
CVPR22(8025-8035)
IEEE DOI
2210
Visualization, Histograms, Image recognition, Costs,
Statistical analysis, Pattern recognition,
Statistical methods
BibRef
Lv, F.[Fangrui],
Liang, J.[Jian],
Li, S.[Shuang],
Zang, B.[Bin],
Liu, C.H.[Chi Harold],
Wang, Z.[Ziteng],
Liu, D.[Di],
Causality Inspired Representation Learning for Domain Generalization,
CVPR22(8036-8046)
IEEE DOI
2210
Representation learning, Data models, Pattern recognition,
Classification algorithms,
Self- semi- meta- unsupervised learning
BibRef
Zhang, J.W.[Jia-Wei],
Wang, X.[Xiang],
Bai, X.[Xiao],
Wang, C.[Chen],
Huang, L.[Lei],
Chen, Y.M.[Yi-Min],
Gu, L.[Lin],
Zhou, J.[Jun],
Harada, T.[Tatsuya],
Hancock, E.R.[Edwin R.],
Revisiting Domain Generalized Stereo Matching Networks from a Feature
Consistency Perspective,
CVPR22(12991-13001)
IEEE DOI
2210
Training, Codes, Training data, Decorrelation, Pattern matching,
3D from multi-view and sensors, Navigation and autonomous driving
BibRef
Liu, B.Y.[Bi-Yang],
Yu, H.M.[Hui-Min],
Qi, G.D.[Guo-Dong],
GraftNet: Towards Domain Generalized Stereo Matching with a
Broad-Spectrum and Task-Oriented Feature,
CVPR22(13002-13011)
IEEE DOI
2210
Training, Costs, Image color analysis,
Multitasking, 3D from multi-view and sensors
BibRef
Chuah, W.Q.[Wei-Qin],
Tennakoon, R.[Ruwan],
Hoseinnezhad, R.[Reza],
Bab-Hadiashar, A.[Alireza],
Suter, D.[David],
ITSA: An Information-Theoretic Approach to Automatic Shortcut
Avoidance and Domain Generalization in Stereo Matching Networks,
CVPR22(13012-13022)
IEEE DOI
2210
Sensitivity, Perturbation methods, Semantics, Feature extraction,
Robustness, Sensors, 3D from multi-view and sensors
BibRef
Galstyan, T.[Tigran],
Harutyunyan, H.[Hrayr],
Khachatrian, H.[Hrant],
Steeg, G.V.[Greg Ver],
Galstyan, A.[Aram],
Failure Modes of Domain Generalization Algorithms,
CVPR22(19055-19064)
IEEE DOI
2210
Training, Representation learning, Machine learning algorithms,
Training data, Focusing, Data models, Machine learning, Datasets and evaluation
BibRef
Nazari, N.H.[Narges Honarvar],
Kovashka, A.[Adriana],
The Role of Shape for Domain Generalization on Sparsely-Textured
Images,
SketchDL22(5116-5126)
IEEE DOI
2210
Bridges, Shape, Transforms, Robustness, Pattern recognition
BibRef
Yüksel, O.K.[Oguz Kaan],
Stich, S.U.[Sebastian U.],
Jaggi, M.[Martin],
Chavdarova, T.[Tatjana],
Semantic Perturbations with Normalizing Flows for Improved
Generalization,
ICCV21(6599-6609)
IEEE DOI
2203
Training, Deep learning, Image coding, Perturbation methods,
Semantics, Neural networks, Optimization and learning methods,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Duboudin, T.[Thomas],
Dellandréa, E.[Emmanuel],
Abgrall, C.[Corentin],
Hénaff, G.[Gilles],
Chen, L.M.[Li-Ming],
Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss
for Single-Source Domain Generalization,
AROW21(51-60)
IEEE DOI
2112
Training, Deep learning, Heuristic algorithms, Neural networks,
Training data, Benchmark testing, Prediction algorithms
BibRef
Guillory, D.[Devin],
Shankar, V.[Vaishaal],
Ebrahimi, S.[Sayna],
Darrell, T.J.[Trevor J.],
Schmidt, L.[Ludwig],
Predicting with Confidence on Unseen Distributions,
ICCV21(1114-1124)
IEEE DOI
2203
Adaptation models, Uncertainty, Filtering, Veins, Training data,
Focusing, Machine learning, Recognition and classification,
Datasets and evaluation
BibRef
Wu, G.[Guile],
Gong, S.G.[Shao-Gang],
Collaborative Optimization and Aggregation for Decentralized Domain
Generalization and Adaptation,
ICCV21(6464-6473)
IEEE DOI
2203
Training, Adaptation models, Data privacy, Collaboration,
Benchmark testing, Predictive models, Data collection,
Recognition and classification
BibRef
Mansilla, L.[Lucas],
Echeveste, R.[Rodrigo],
Milone, D.H.[Diego H.],
Ferrante, E.[Enzo],
Domain Generalization via Gradient Surgery,
ICCV21(6610-6618)
IEEE DOI
2203
Training, Surgery, Interference,
Picture archiving and communication systems, Data models,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Gong, Y.[Yunye],
Lin, X.[Xiao],
Yao, Y.[Yi],
Dietterich, T.G.[Thomas G.],
Divakaran, A.[Ajay],
Gervasio, M.[Melinda],
Confidence Calibration for Domain Generalization under Covariate
Shift,
ICCV21(8938-8947)
IEEE DOI
2203
Training, Adaptation models, Upper bound, Temperature,
Linear regression, Clustering algorithms, and ethics in vision
BibRef
Kim, D.[Daehee],
Yoo, Y.[Youngjun],
Park, S.H.[Seung-Hyun],
Kim, J.[Jinkyu],
Lee, J.[Jaekoo],
SelfReg: Self-supervised Contrastive Regularization for Domain
Generalization,
ICCV21(9599-9608)
IEEE DOI
2203
Training, Deep learning, Computational modeling,
Perturbation methods, Benchmark testing, Feature extraction,
Efficient training and inference methods
BibRef
Sariyildiz, M.B.[Mert Bulent],
Kalantidis, Y.[Yannis],
Larlus, D.[Diane],
Alahari, K.[Karteek],
Concept Generalization in Visual Representation Learning,
ICCV21(9609-9619)
IEEE DOI
2203
Training, Visualization, Adaptation models, Current transformers,
Search methods, Semantics, Supervised learning,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Shankar, V.[Vaishaal],
Dave, A.[Achal],
Roelofs, R.[Rebecca],
Ramanan, D.[Deva],
Recht, B.[Benjamin],
Schmidt, L.[Ludwig],
Do Image Classifiers Generalize Across Time?,
ICCV21(9641-9649)
IEEE DOI
2203
Analytical models, Perturbation methods, Speech recognition,
Predictive models, Benchmark testing, Robustness, Adversarial learning
BibRef
Paul, S.[Soumava],
Dutta, T.[Titir],
Biswas, S.[Soma],
Universal Cross-Domain Retrieval:
Generalizing Across Classes and Domains,
ICCV21(12036-12044)
IEEE DOI
2203
Training, Bridges, Protocols, Semantics, Task analysis, Testing,
Image and video retrieval, Recognition and classification
BibRef
Wang, Z.J.[Zi-Jian],
Luo, Y.[Yadan],
Qiu, R.[Ruihong],
Huang, Z.[Zi],
Baktashmotlagh, M.[Mahsa],
Learning to Diversify for Single Domain Generalization,
ICCV21(814-823)
IEEE DOI
2203
Training, Upper bound, Codes, Semantics, Benchmark testing,
Optimization, Recognition and classification,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Narayanan, M.[Maruthi],
Rajendran, V.[Vickram],
Kimia, B.[Benjamin],
Shape-Biased Domain Generalization via Shock Graph Embeddings,
ICCV21(1295-1305)
IEEE DOI
2203
Training, Sensitivity, Shape, Electric shock, Computational modeling,
Feature extraction, Recognition and classification,
grouping and shape
BibRef
Li, P.[Pan],
Li, D.[Da],
Li, W.[Wei],
Gong, S.G.[Shao-Gang],
Fu, Y.W.[Yan-Wei],
Hospedales, T.M.[Timothy M.],
A Simple Feature Augmentation for Domain Generalization,
ICCV21(8866-8875)
IEEE DOI
2203
Training, Codes, Computational modeling, Gaussian noise,
Stochastic processes, Representation learning
BibRef
Tang, Z.Q.[Zhi-Qiang],
Gao, Y.H.[Yun-He],
Zhu, Y.[Yi],
Zhang, Z.[Zhi],
Li, M.[Mu],
Metaxas, D.N.[Dimitris N.],
CrossNorm and SelfNorm for Generalization under Distribution Shifts,
ICCV21(52-61)
IEEE DOI
2203
Training, Bridges, Codes, Robustness, Task analysis,
Recognition and classification, Vision applications and systems
BibRef
Azimi, F.[Fatemeh],
Palacio, S.[Sebastian],
Raue, F.[Federico],
Hees, J.[Jörn],
Bertinetto, L.[Luca],
Dengel, A.[Andreas],
Self-Supervised Test-Time Adaptation on Video Data,
WACV22(2603-2612)
IEEE DOI
2202
Adapt due to changes in video.
Training, Adaptation models, Target tracking,
Computational modeling, Video sequences, Training data,
Vision Systems and Applications
BibRef
Mangla, P.[Puneet],
Chandhok, S.[Shivam],
Balasubramanian, V.N.[Vineeth N.],
Khan, F.S.[Fahad Shahbaz],
COCOA: Context-Conditional Adaptation for Recognizing Unseen Classes
in Unseen Domains,
WACV22(1618-1627)
IEEE DOI
2202
Visualization, Adaptation models, Fuses, Semantics,
Buildings, Benchmark testing, Transfer, Few-shot,
Semi- and Un- supervised Learning Deep Learning
BibRef
Kim, J.[Jin],
Lee, J.Y.[Ji-Young],
Park, J.[Jungin],
Min, D.B.[Dong-Bo],
Sohn, K.H.[Kwang-Hoon],
Self-Balanced Learning for Domain Generalization,
ICIP21(779-783)
IEEE DOI
2201
Training, Degradation, Adaptive systems, Image processing,
Training data, Predictive models, Domain generalization,
meta-learning
BibRef
Le, H.S.[Hoang Son],
Akmeliawati, R.[Rini],
Carneiro, G.[Gustavo],
Combining Data Augmentation and Domain Distance Minimisation to
Reduce Domain Generalisation Error,
DICTA21(01-08)
IEEE DOI
2201
Training, Adaptation models, Upper bound, Digital images,
Benchmark testing, Minimization, Picture archiving and communication systems
BibRef
Pandey, P.[Prashant],
Raman, M.[Mrigank],
Varambally, S.[Sumanth],
Ap, P.[Prathosh],
Generalization on Unseen Domains via Inference-time Label-Preserving
Target Projections,
CVPR21(12919-12928)
IEEE DOI
2111
Manifolds, Training, Machine learning,
Extraterrestrial measurements, Data models, Pattern recognition
BibRef
Li, G.R.[Guang-Rui],
Kang, G.L.[Guo-Liang],
Zhu, Y.[Yi],
Wei, Y.C.[Yun-Chao],
Yang, Y.[Yi],
Domain Consensus Clustering for Universal Domain Adaptation,
CVPR21(9752-9761)
IEEE DOI
2111
Benchmark testing, Pattern recognition
BibRef
Dubey, A.[Abhimanyu],
Ramanathan, V.[Vignesh],
Pentland, A.[Alex],
Mahajan, D.[Dhruv],
Adaptive Methods for Real-World Domain Generalization,
CVPR21(14335-14344)
IEEE DOI
2111
Training, Heart, Adaptation models,
Machine learning, Benchmark testing, Predictive models
BibRef
Choi, S.[Sungha],
Jung, S.[Sanghun],
Yun, H.[Huiwon],
Kim, J.T.[Joanne T.],
Kim, S.[Seungryong],
Choo, J.[Jaegul],
RobustNet: Improving Domain Generalization in Urban-Scene
Segmentation via Instance Selective Whitening,
CVPR21(11575-11585)
IEEE DOI
2111
Training, Deep learning, Image segmentation, Codes,
Robustness, Pattern recognition
See also Study of RobustNet, a Domain Generalization Method for Semantic Segmentation, A.
BibRef
Fan, X.J.[Xin-Jie],
Wang, Q.F.[Qi-Fei],
Ke, J.J.[Jun-Jie],
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CVPR21(8204-8213)
IEEE DOI
2111
Training, Adaptation models, Adaptive systems, Neural networks,
Benchmark testing, Tools, Data models
BibRef
Huang, J.X.[Jia-Xing],
Guan, D.[Dayan],
Xiao, A.[Aoran],
Lu, S.J.[Shi-Jian],
FSDR: Frequency Space Domain Randomization for Domain Generalization,
CVPR21(6887-6898)
IEEE DOI
2111
Training, Image segmentation, Frequency-domain analysis, Semantics,
Transform coding, Aerospace electronics, Frequency conversion
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CVPR21(1084-1093)
IEEE DOI
2111
Benchmark testing, Pattern recognition
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Huang, Z.[Ziyao],
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Xia, B.[Boyang],
Progressive Domain Expansion Network for Single Domain Generalization,
CVPR21(224-233)
IEEE DOI
2111
Training, Handheld computers, Computational modeling, Semantics,
Transforms, Performance gain, Generators
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Eguchi, S.[Shu],
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Output augmentation works well without any domain knowledge,
MVA21(1-5)
DOI Link
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To improve generalization performance, without requiring data augmentation.
Training data, Task analysis, Image classification
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Rethinking Domain Generalization Baselines,
ICPR21(9227-9233)
IEEE DOI
2105
Deep learning, Writing, Tools, Robustness, Data models,
Pattern recognition, Standards
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Respecting Domain Relations: Hypothesis Invariance for Domain
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ICPR21(9756-9763)
IEEE DOI
2105
Training, Estimation, Distributed databases, Probabilistic logic,
Pattern recognition, Reliability, Domain generalization,
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ECCV20(XXII:68-83).
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2011
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ECCV20(X:200-216).
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ECCV20(IX:301-318).
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2011
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ECCV20(IX:159-176).
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2011
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Learning to Learn Single Domain Generalization,
CVPR20(12553-12562)
IEEE DOI
2008
Training, Task analysis, Transportation, Adaptation models,
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CRV20(93-100)
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Digits, faces, pedestrians.
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Domain Randomization and Pyramid Consistency: Simulation-to-Real
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ICCV19(2100-2110)
IEEE DOI
2004
feature extraction, image representation,
image segmentation, learning (artificial intelligence),
Adaptation models
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ICCV19(1446-1455)
IEEE DOI
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convolutional neural nets, feature extraction,
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Domain Generalization with Domain-Specific Aggregation Modules,
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1905
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ICCV17(5716-5726)
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1802
feature extraction, image representation,
learning (artificial intelligence), statistical distributions,
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multi-Task Learning, Multiple Tasks, Transfer Learning, Domain Adaption .