14.1.8.5 Domain Generalization

Chapter Contents (Back)
Domain Adaption. Domain Generalization.
See also Pre-Training.

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.T.[Sen-Tao], Wang, L.[Lei], Hong, Z.J.[Zi-Jie], 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

Tian, C.X.[Chris Xing], Li, H.L.[Hao-Liang], Xie, X.F.[Xiao-Fei], Liu, Y.[Yang], Wang, S.Q.[Shi-Qi],
Neuron Coverage-Guided Domain Generalization,
PAMI(45), No. 1, January 2023, pp. 1302-1311.
IEEE DOI 2212
Neurons, Training, Task analysis, Semantics, Computer bugs, Training data, Software, Gradient similarity, neuron coverage, out-of-distribution BibRef

Segu, M.[Mattia], Tonioni, A.[Alessio], Tombari, F.[Federico],
Batch normalization embeddings for deep domain generalization,
PR(135), 2023, pp. 109115.
Elsevier DOI 2212
Domain generalization, Domain representation learning, Learning from multiple sources BibRef

Wang, Y.Q.[Yun-Qi], Liu, F.[Furui], Chen, Z.T.[Zhi-Tang], Wu, Y.C.[Yik-Chung], Hao, J.[Jianye], Chen, G.Y.[Guang-Yong], Heng, P.A.[Pheng-Ann],
Contrastive-ACE: Domain Generalization Through Alignment of Causal Mechanisms,
IP(32), 2023, pp. 235-250.
IEEE DOI 2301
Training, Feature extraction, Data models, Task analysis, Training data, Predictive models, Optimization, Causal inference, deep learning BibRef

Yuan, J.K.[Jun-Kun], Ma, X.[Xu], Chen, D.F.[De-Fang], Kuang, K.[Kun], Wu, F.[Fei], Lin, L.F.[Lan-Fen],
Domain-Specific Bias Filtering for Single Labeled Domain Generalization,
IJCV(131), No. 2, February 2023, pp. 552-571.
Springer DOI 2301
BibRef

Liu, Y.J.[Ya-Jing], Xiong, Z.W.[Zhi-Wei], Li, Y.[Ya], Tian, X.[Xinmei], Zha, Z.J.[Zheng-Jun],
Domain Generalization Via Encoding and Resampling in a Unified Latent Space,
MultMed(25), 2023, pp. 126-139.
IEEE DOI 2301
Feature extraction, Training, Perturbation methods, Encoding, Gaussian distribution, Aerospace electronics, Data mining, adversarial examples BibRef

Yang, Y.H.[Yan-Hua], Zhang, X.Z.[Xiao-Zhe], Yang, M.[Muli], Deng, C.[Cheng],
Adaptive Bias-Aware Feature Generation for Generalized Zero-Shot Learning,
MultMed(25), 2023, pp. 280-290.
IEEE DOI 2301
Visualization, Semantics, Generators, Training, Generative adversarial networks, Data models, Benchmark testing, bias problem BibRef

Luna, E.[Elena], SanMiguel, J.C.[Juan C.], Martínez, J.M.[José M.], Carballeira, P.[Pablo],
Graph Neural Networks for Cross-Camera Data Association,
CirSysVideo(33), No. 2, February 2023, pp. 589-601.
IEEE DOI 2302
Cameras, Task analysis, Image edge detection, Message passing, Graph neural networks, Feature extraction, Data association, message passing network BibRef

Zhou, K.Y.[Kai-Yang], Liu, Z.W.[Zi-Wei], Qiao, Y.[Yu], Xiang, T.[Tao], Loy, C.C.[Chen Change],
Domain Generalization: A Survey,
PAMI(45), No. 4, April 2023, pp. 4396-4415.
IEEE DOI 2303
Survey, Domain Generalization. Data models, Speech recognition, Adaptation models, Face recognition, Soft sensors, Handwriting recognition, machine learning BibRef

Xia, H.F.[Hai-Feng], Jing, T.[Taotao], Ding, Z.M.[Zheng-Ming],
Generative Inference Network for Imbalanced Domain Generalization,
IP(32), 2023, pp. 1694-1704.
IEEE DOI 2303
Feature extraction, Training, Task analysis, Semantics, Robustness, Data models, Visualization, knowledge transfer BibRef

Xu, Q.W.[Qin-Wei], Zhang, R.P.[Rui-Peng], Fan, Z.Q.[Zi-Qing], Wang, Y.F.[Yan-Feng], Wu, Y.Y.[Yi-Yan], Zhang, Y.[Ya],
Fourier-based augmentation with applications to domain generalization,
PR(139), 2023, pp. 109474.
Elsevier DOI 2304
Domain shift, Domain generalization, Fourier-based augmentation, Consistency training BibRef

Zhu, S.[Sihan], Wu, C.[Chen], Du, B.[Bo], Zhang, L.P.[Liang-Pei],
Style and content separation network for remote sensing image cross-scene generalization,
PandRS(201), 2023, pp. 1-11.
Elsevier DOI 2307
Cross-scene classification, Deep learning, Domain generalization, Style manipulation BibRef

Zhou, K.Y.[Kai-Yang], Loy, C.C.[Chen Change], Liu, Z.W.[Zi-Wei],
Semi-Supervised Domain Generalization with Stochastic StyleMatch,
IJCV(131), No. 9, September 2023, pp. 2377-2387.
Springer DOI 2308
BibRef

Zhang, X.[Xin], Chen, Y.C.[Ying-Cong],
Adaptive Domain Generalization Via Online Disagreement Minimization,
IP(32), 2023, pp. 4247-4258.
IEEE DOI 2308
Adaptation models, Feature extraction, Training, Predictive models, Data models, Minimization, Entropy, Domain shift, consistency regularization BibRef

Zhang, L.[Lei], Du, Y.J.[Ying-Jun], Shen, J.Y.[Jia-Yi], Zhen, X.T.[Xian-Tong],
Learning to Learn With Variational Inference for Cross-Domain Image Classification,
MultMed(25), 2023, pp. 3319-3328.
IEEE DOI 2309
BibRef

Du, Y.J.[Ying-Jun], Xu, J.[Jun], Xiong, H.[Huan], Qiu, Q.A.[Qi-Ang], Zhen, X.T.[Xian-Tong], Snoek, C.G.M.[Cees G. M.], Shao, L.[Ling],
Learning to Learn with Variational Information Bottleneck for Domain Generalization,
ECCV20(X:200-216).
Springer DOI 2011
BibRef

Chuah, W.Q.[Wei-Qin], Tennakoon, R.[Ruwan], Hoseinnezhad, R.[Reza], Suter, D.[David], Bab-Hadiashar, A.[Alireza],
An Information-Theoretic Method to Automatic Shortcut Avoidance and Domain Generalization for Dense Prediction Tasks,
PAMI(45), No. 9, September 2023, pp. 10615-10631.
IEEE DOI 2309
BibRef

Hong, M.Y.[Ming-Yao], Zhang, X.F.[Xin-Feng], Li, G.R.[Guo-Rong], Huang, Q.M.[Qing-Ming],
Multi-Modal Multi-Grained Embedding Learning for Generalized Zero-Shot Video Classification,
CirSysVideo(33), No. 10, October 2023, pp. 5959-5972.
IEEE DOI 2310
BibRef

Zhang, J.[Jiao], Zhang, X.Y.[Xu-Yao], Wang, C.[Chuang], Liu, C.L.[Cheng-Lin],
Deep representation learning for domain generalization with information bottleneck principle,
PR(143), 2023, pp. 109737.
Elsevier DOI 2310
Domain generalization, Information bottleneck, Representation learning BibRef

Qin, T.[Tiexin], Wang, S.Q.[Shi-Qi], Li, H.L.[Hao-Liang],
Evolving Domain Generalization via Latent Structure-Aware Sequential Autoencoder,
PAMI(45), No. 12, December 2023, pp. 14514-14527.
IEEE DOI 2311
BibRef

Hu, J.J.[Jia-Jun], Qi, L.[Lei], Zhang, J.[Jian], Shi, Y.H.[Ying-Huan],
Domain generalization via Inter-domain Alignment and Intra-domain Expansion,
PR(146), 2024, pp. 110029.
Elsevier DOI 2311
Domain generalization, Contrastive learning, Image recognition BibRef

Gholami, B.[Behnam], El-Khamy, M.[Mostafa], Song, K.B.[Kee-Bong],
Latent Feature Disentanglement for Visual Domain Generalization,
IP(32), 2023, pp. 5751-5763.
IEEE DOI 2311
BibRef

Li, J.W.[Jing-Wei], Li, Y.[Yuan], Wang, H.J.[Huan-Jie], Liu, C.B.[Cheng-Bao], Tan, J.[Jie],
Exploring Explicitly Disentangled Features for Domain Generalization,
CirSysVideo(33), No. 11, November 2023, pp. 6360-6373.
IEEE DOI 2311
BibRef

Choi, J.[Jaehyun], Seong, H.S.[Hyun Seok], Park, S.[Sanguk], Heo, J.P.[Jae-Pil],
TCX: Texture and channel swappings for domain generalization,
PRL(175), 2023, pp. 74-80.
Elsevier DOI 2311
Deep learning, Domain generalization, Image classification, Model regularization BibRef

Zhao, Q.J.[Qing-Jie], Wang, X.[Xin], Wang, B.[Binglu], Wang, L.[Lei], Liu, W.[Wangwang], Li, S.S.[Shan-Shan],
A Dual-Attention Deep Discriminative Domain Generalization Model for Hyperspectral Image Classification,
RS(15), No. 23, 2023, pp. 5492.
DOI Link 2312
BibRef

Li, Y.M.[Yu-Meng], Zhang, D.[Dan], Keuper, M.[Margret], Khoreva, A.[Anna],
Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization,
IJCV(132), No. 2, February 2024, pp. 446-465.
Springer DOI 2402
BibRef
Earlier:
Intra-Source Style Augmentation for Improved Domain Generalization,
WACV23(509-519)
IEEE DOI 2302
Training, Semantic segmentation, Semantics, Layout, Training data, Predictive models, Network architecture, image and video synthesis BibRef

Wang, M.Z.[Meng-Zhu], Liu, Y.H.[Yue-Hua], Yuan, J.L.[Jian-Long], Wang, S.S.[Shan-Shan], Wang, Z.B.[Zhi-Bin], Wang, W.[Wei],
Inter-Class and Inter-Domain Semantic Augmentation for Domain Generalization,
IP(33), 2024, pp. 1338-1347.
IEEE DOI 2402
Semantics, Data augmentation, Training, Self-supervised learning, Painting, Data models, inter-domain BibRef

Zhou, K.Y.[Kai-Yang], Yang, Y.X.[Yong-Xin], Qiao, Y.[Yu], Xiang, T.[Tao],
MixStyle Neural Networks for Domain Generalization and Adaptation,
IJCV(132), No. 3, March 2024, pp. 822-836.
Springer DOI 2402
BibRef

Qi, L.[Lei], Yang, H.P.[Hong-Peng], Shi, Y.[Yinghuan], Geng, X.[Xin],
NormAUG: Normalization-Guided Augmentation for Domain Generalization,
IP(33), 2024, pp. 1419-1431.
IEEE DOI 2402
Training, Training data, Data augmentation, Data models, Feature extraction, Ensemble learning, Task analysis, domain-shift BibRef

Chen, Z.[Zining], Wang, W.Q.[Wei-Qiu], Zhao, Z.C.[Zhi-Cheng], Su, F.[Fei], Men, A.[Aidong], Dong, Y.[Yuan],
Instance Paradigm Contrastive Learning for Domain Generalization,
CirSysVideo(34), No. 2, February 2024, pp. 1032-1042.
IEEE DOI 2402
Prototypes, Training, Task analysis, Learning systems, Optimization, Excavation, Representation learning, Instance paradigm, domain generalization BibRef

Lin, L.J.[Luo-Jun], Xie, H.[Han], Sun, Z.S.[Zhi-Shu], Chen, W.J.[Wei-Jie], Liu, W.X.[Wen-Xi], Yu, Y.L.[Yuan-Long], Zhang, L.[Lei],
Semi-supervised domain generalization with evolving intermediate domain,
PR(149), 2024, pp. 110280.
Elsevier DOI 2403
Domain generalization, Unsupervised domain adaptation, Semi-supervised learning, Transfer learning BibRef

Zhang, Y.B.[Ya-Bin], Deng, B.[Bin], Jia, K.[Kui], Zhang, L.[Lei],
Label Propagation with Augmented Anchors: A Simple Semi-supervised Learning Baseline for Unsupervised Domain Adaptation,
ECCV20(IV:781-797).
Springer DOI 2011
BibRef

Noori, M.[Mehrdad], Cheraghalikhani, M.[Milad], Bahri, A.[Ali], Vargas-Hakim, G.A.[Gustavo A.], Osowiechi, D.[David], Ben Ayed, I.[Ismail], Desrosiers, C.[Christian],
TFS-ViT: Token-level feature stylization for domain generalization,
PR(149), 2024, pp. 110213.
Elsevier DOI 2403
Deep learning, Domain generalization, Vision transformer, Feature stylization BibRef

Wang, N.[Na], Qi, L.[Lei], Guo, J.T.[Jin-Tao], Shi, Y.H.[Ying-Huan], Gao, Y.[Yang],
Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations,
IP(33), 2024, pp. 1627-1642.
IEEE DOI Code:
WWW Link. 2403
Correlation, Feature extraction, Task analysis, Tail, Semantics, Training, Frequency-domain analysis, Domain generalization, MLPs BibRef

Bissoto, A.[Alceu], Barata, C.[Catarina], Valle, E.[Eduardo], Avila, S.[Sandra],
Even small correlation and diversity shifts pose dataset-bias issues,
PRL(179), 2024, pp. 87-93.
Elsevier DOI 2403
Distribution shift, Domain generalization, Spurious features, Medical image analysis, Deep learning BibRef

Kang, J.H.[Jin-Ho], Kim, T.[Taero], Kim, Y.[Yewon], Oh, C.[Changdae], Jung, J.Y.[Ji-Young], Chang, R.[Rakwoo], Song, K.[Kyungwoo],
Bibimbap: Pre-trained models ensemble for Domain Generalization,
PR(151), 2024, pp. 110391.
Elsevier DOI 2404
Transfer learning, Molecular classification, Domain generalization, Weight averaging, Ensemble learning, Chemical dataset BibRef

Liu, L.[Lina], Song, X.B.[Xi-Bin], Wang, M.M.[Meng-Meng], Dai, Y.C.[Yu-Chao], Liu, Y.[Yong], Zhang, L.J.[Liang-Jun],
AGDF-Net: Learning Domain Generalizable Depth Features With Adaptive Guidance Fusion,
PAMI(46), No. 5, May 2024, pp. 3137-3155.
IEEE DOI 2404
Estimation, Feature extraction, Adaptive systems, Task analysis, Navigation, Synthetic data, Training, Depth estimation, adaptive guidance fusion BibRef

Wang, Z.[Zhen], Bai, L.[Lan], Shao, Y.[Yuanhai],
Generalization Memorization Machine with Zero Empirical Risk for Classification,
PR(152), 2024, pp. 110469.
Elsevier DOI 2405
Classification, Support vector machine, Generalization memorization mechanism, Memory machine, Generalization memorization kernel BibRef

Cheraghalikhani, M.[Milad], Noori, M.[Mehrdad], Osowiechi, D.[David], Hakim, G.A.V.[Gustavo A. Vargas], Ben Ayed, I.[Ismail], Desrosiers, C.[Christian],
Structure-aware feature stylization for domain generalization,
CVIU(244), 2024, pp. 104016.
Elsevier DOI 2405
Computer vision, Image classification, Domain generalization BibRef

Bai, W.J.[Wen-Jing], Zhang, Y.Z.[Yun-Zhou], Wang, L.[Li], Liu, W.[Wei], Hu, J.[Jun], Huang, G.[Guan],
SADGFeat: Learning local features with layer spatial attention and domain generalization,
IVC(146), 2024, pp. 105033.
Elsevier DOI 2405
Local feature learning, Domain generalization, Spatial attention, Image matching, Visual localization BibRef


Liu, R.[Ran], Khose, S.[Sahil], Xiao, J.Y.[Jing-Yun], Sathidevi, L.[Lakshmi], Ramnath, K.[Keerthan], Kira, Z.[Zsolt], Dyer, E.L.[Eva L.],
LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration,
WACV24(2657-2667)
IEEE DOI Code:
WWW Link. 2404
Degradation, Deep learning, Training, Adaptation models, Training data, Space mapping, Self-supervised learning, Algorithms, Biomedical / healthcare / medicine BibRef

Bose, S.[Shirsha], Jha, A.[Ankit], Fini, E.[Enrico], Singha, M.[Mainak], Ricci, E.[Elisa], Banerjee, B.[Biplab],
StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization,
WACV24(5530-5540)
IEEE DOI 2404
Visualization, Limiting, Benchmark testing, Feature extraction, Task analysis, Algorithms, Image recognition and understanding BibRef

Chuah, W.[WeiQin], Tennakoon, R.[Ruwan], Hoseinnezhad, R.[Reza], Suter, D.[David], Bab-Hadiashar, A.[Alireza],
Single Domain Generalization via Normalised Cross-correlation Based Convolutions,
WACV24(1741-1750)
IEEE DOI 2404
Deep learning, Sensitivity, Convolution, Computational modeling, Semantics, Training data, Data augmentation, Algorithms BibRef

Bele, P.[Prathmesh], Bundele, V.[Valay], Bhattacharya, A.[Avigyan], Jha, A.[Ankit], Roig, G.[Gemma], Banerjee, B.[Biplab],
Learning Class and Domain Augmentations for Single-Source Open-Domain Generalization,
WACV24(1805-1815)
IEEE DOI 2404
Training, Measurement, Benchmark testing, Algorithms, Machine learning architectures, formulations, and algorithms, Image recognition and understanding BibRef

Zhang, Z.[Zheyuan], Wang, B.[Bin], Jha, D.[Debesh], Demir, U.[Ugur], Bagci, U.[Ulas],
Domain Generalization with Correlated Style Uncertainty,
WACV24(1989-1998)
IEEE DOI Code:
WWW Link. 2404
Deep learning, Interpolation, Uncertainty, Correlation, Computational modeling, Source coding, Algorithms, Image recognition and understanding BibRef

Aminbeidokhti, M.[Masih], Peña, F.A.G.[Fidel A. Guerrero], Medeiros, H.R.[Heitor Rapela], Dubail, T.[Thomas], Granger, E.[Eric], Pedersoli, M.[Marco],
Domain Generalization by Rejecting Extreme Augmentations,
WACV24(2204-2214)
IEEE DOI Code:
WWW Link. 2404
Training, Deep learning, Codes, Computational modeling, Data augmentation, Picture archiving and communication systems, Image recognition and understanding BibRef

Nguyen, T.[Toan], Do, K.[Kien], Duong, B.[Bao], Nguyen, T.[Thin],
Domain Generalisation via Risk Distribution Matching,
WACV24(2778-2787)
IEEE DOI 2404
Training, Aggregates, Buildings, Benchmark testing, Approximation algorithms, Computational efficiency, Algorithms BibRef

Singhal, U.[Utkarsh], Esteves, C.[Carlos], Makadia, A.[Ameesh], Yu, S.X.[Stella X.],
Learning to Transform for Generalizable Instance-wise Invariance,
ICCV23(6188-6198)
IEEE DOI 2401
BibRef

Guo, J.T.[Jin-Tao], Qi, L.[Lei], Shi, Y.[Yinghuan],
DomainDrop: Suppressing Domain-Sensitive Channels for Domain Generalization,
ICCV23(19057-19067)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhao, B.C.[Bing-Chen], Aodha, O.M.[Oisin Mac],
Incremental Generalized Category Discovery,
ICCV23(19080-19090)
IEEE DOI 2401
BibRef

Jing, M.M.[Meng-Meng], Zhen, X.T.[Xian-Tong], Li, J.J.[Jing-Jing], Snoek, C.G.M.[Cees G. M.],
Order-preserving Consistency Regularization for Domain Adaptation and Generalization,
ICCV23(18870-18881)
IEEE DOI 2401
BibRef

Cheng, S.[Sheng], Gokhale, T.[Tejas], Yang, Y.Z.[Ye-Zhou],
Adversarial Bayesian Augmentation for Single-Source Domain Generalization,
ICCV23(11366-11376)
IEEE DOI Code:
WWW Link. 2401
BibRef

Huang, Z.Y.[Ze-Yi], Zhou, A.[Andy], Lin, Z.J.[Zi-Jian], Cai, M.[Mu], Wang, H.H.[Hao-Han], Lee, Y.J.[Yong Jae],
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance,
ICCV23(11651-11661)
IEEE DOI 2401
BibRef

Jiang, X.Y.[Xue-Ying], Huang, J.X.[Jia-Xing], Jin, S.[Sheng], Lu, S.J.[Shi-Jian],
Domain Generalization via Balancing Training Difficulty and Model Capability,
ICCV23(18947-18957)
IEEE DOI 2401
BibRef

Hemati, S.[Sobhan], Zhang, G.J.[Guo-Jun], Estiri, A.[Amir], Chen, X.[Xi],
Understanding Hessian Alignment for Domain Generalization,
ICCV23(18958-18968)
IEEE DOI 2401
BibRef

Hu, L.[Lanqing], Kan, M.[Meina], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
DandelionNet: Domain Composition with Instance Adaptive Classification for Domain Generalization,
ICCV23(19004-19013)
IEEE DOI 2401
BibRef

Huang, Z.[Zenan], Wang, H.[Haobo], Zhao, J.[Junbo], Zheng, N.G.[Neng-Gan],
iDAG: Invariant DAG Searching for Domain Generalization,
ICCV23(19112-19122)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chattopadhyay, P.[Prithvijit], Sarangmath, K.[Kartik], Vijaykumar, V.[Vivek], Hoffman, J.[Judy],
Pasta: Proportional Amplitude Spectrum Training Augmentation for Syn-to-Real Domain Generalization,
ICCV23(19231-19243)
IEEE DOI 2401
BibRef

Chen, C.Q.[Chao-Qi], Tang, L.[Luyao], Tao, L.[Leitian], Zhou, H.Y.[Hong-Yu], Huang, Y.[Yue], Han, X.G.[Xiao-Guang], Yu, Y.Z.[Yi-Zhou],
Activate and Reject: Towards Safe Domain Generalization under Category Shift,
ICCV23(11518-11529)
IEEE DOI 2401
BibRef

Michalkiewicz, M.[Mateusz], Faraki, M.[Masoud], Yu, X.[Xiang], Chandraker, M.[Manmohan], Baktashmotlagh, M.[Mahsa],
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters,
ICCV23(6154-6165)
IEEE DOI 2401
BibRef

Zhang, X.X.[Xing-Xuan], Xu, R.Z.[Ren-Zhe], Yu, H.[Han], Dong, Y.C.[Yan-Cheng], Tian, P.F.[Peng-Fei], Cui, P.[Peng],
Flatness-Aware Minimization for Domain Generalization,
ICCV23(5166-5179)
IEEE DOI 2401
BibRef

Chen, L.[Liang], Zhang, Y.[Yong], Song, Y.B.[Yi-Bing], van den Hengel, A.J.[Anton J.], Liu, L.Q.[Ling-Qiao],
Domain Generalization via Rationale Invariance,
ICCV23(1751-1760)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, C.M.[Chen-Ming], Zhang, D.[Daoan], Huang, W.J.[Wen-Jian], Zhang, J.G.[Jian-Guo],
Cross Contrasting Feature Perturbation for Domain Generalization,
ICCV23(1327-1337)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gholami, B.[Behnam], El-Khamy, M.[Mostafa], Song, K.B.[Kee-Bong],
Domain invariant regularization by disentangling content and style Features for visual domain generalization,
ICIP23(1525-1529)
IEEE DOI 2312
BibRef

Liu, F.F.[Fang-Fu], Zhang, C.B.[Chu-Bin], Zheng, Y.[Yu], Duan, Y.[Yueqi],
Semantic Ray: Learning a Generalizable Semantic Field with Cross-Reprojection Attention,
CVPR23(17386-17396)
IEEE DOI 2309
BibRef

Lv, F.R.[Fang-Rui], Liang, J.[Jian], Li, S.[Shuang], Zhang, J.M.[Jin-Ming], Liu, D.[Di],
Improving Generalization with Domain Convex Game,
CVPR23(24315-24324)
IEEE DOI 2309
BibRef

Leclerc, G.[Guillaume], Ilyas, A.[Andrew], Engstrom, L.[Logan], Park, S.M.[Sung Min], Salman, H.[Hadi], Madry, A.[Aleksander],
FFCV: Accelerating Training by Removing Data Bottlenecks,
CVPR23(12011-12020)
IEEE DOI 2309
BibRef

Sarfi, A.M.[Amir M.], Karimpour, Z.[Zahra], Chaudhary, M.[Muawiz], Khalid, N.M.[Nasir M.], Ravanelli, M.[Mirco], Mudur, S.[Sudhir], Belilovsky, E.[Eugene],
Simulated Annealing in Early Layers Leads to Better Generalization,
CVPR23(20205-20214)
IEEE DOI 2309
BibRef

Xu, Q.[Qinwei], Zhang, R.P.[Rui-Peng], Wu, Y.Y.[Yi-Yan], Zhang, Y.[Ya], Liu, N.[Ning], Wang, Y.F.[Yan-Feng],
SimDE: A Simple Domain Expansion Approach for Single-source Domain Generalization,
L3D-IVU23(4798-4808)
IEEE DOI 2309
BibRef

Chen, J.[Jin], Gao, Z.[Zhi], Wu, X.X.[Xin-Xiao], Luo, J.B.[Jie-Bo],
Meta-Causal Learning for Single Domain Generalization,
CVPR23(7683-7692)
IEEE DOI 2309
BibRef

Choi, S.[Seokeon], Das, D.[Debasmit], Choi, S.[Sungha], Yang, S.[Seunghan], Park, H.[Hyunsin], Yun, S.[Sungrack],
Progressive Random Convolutions for Single Domain Generalization,
CVPR23(10312-10322)
IEEE DOI 2309
BibRef

Lee, S.[Sangrok], Bae, J.[Jongseong], Kim, H.Y.[Ha Young],
Decompose, Adjust, Compose: Effective Normalization by Playing with Frequency for Domain Generalization,
CVPR23(11776-11785)
IEEE DOI 2309
BibRef

Lin, S.Q.[Shi-Qi], Zhang, Z.Z.[Zhi-Zheng], Huang, Z.P.[Zhi-Peng], Lu, Y.[Yan], Lan, C.L.[Cui-Ling], Chu, P.[Peng], You, Q.Z.[Quan-Zeng], Wang, J.[Jiang], Liu, Z.C.[Zi-Cheng], Parulkar, A.[Amey], Navkal, V.[Viraj], Chen, Z.B.[Zhi-Bo],
Deep Frequency Filtering for Domain Generalization,
CVPR23(11797-11807)
IEEE DOI 2309
BibRef

Zhang, X.X.[Xing-Xuan], He, Y.[Yue], Xu, R.Z.[Ren-Zhe], Yu, H.[Han], Shen, Z.[Zheyan], Cui, P.[Peng],
NICO++: Towards Better Benchmarking for Domain Generalization,
CVPR23(16036-16047)
IEEE DOI 2309
BibRef

Jain, S.[Samyak], Addepalli, S.[Sravanti], Sahu, P.K.[Pawan Kumar], Dey, P.[Priyam], Babu, R.V.[R. Venkatesh],
DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks,
CVPR23(16048-16059)
IEEE DOI 2309
BibRef

Guo, J.T.[Jin-Tao], Wang, N.[Na], Qi, L.[Lei], Shi, Y.[Yinghuan],
ALOFT: A Lightweight MLP-Like Architecture with Dynamic Low-Frequency Transform for Domain Generalization,
CVPR23(24132-24141)
IEEE DOI 2309
BibRef

Qu, S.Q.[San-Qing], Pan, Y.W.[Ying-Wei], Chen, G.[Guang], Yao, T.[Ting], Jiang, C.J.[Chang-Jun], Mei, T.[Tao],
Modality-Agnostic Debiasing for Single Domain Generalization,
CVPR23(24142-24151)
IEEE DOI 2309
BibRef

Chen, L.[Liang], Zhang, Y.[Yong], Song, Y.B.[Yi-Bing], Shan, Y.[Ying], Liu, L.Q.[Ling-Qiao],
Improved Test-Time Adaptation for Domain Generalization,
CVPR23(24172-24182)
IEEE DOI 2309
BibRef

Wang, P.F.[Peng-Fei], Zhang, Z.X.[Zhao-Xiang], Lei, Z.[Zhen], Zhang, L.[Lei],
Sharpness-Aware Gradient Matching for Domain Generalization,
CVPR23(3769-3778)
IEEE DOI 2309
BibRef

Ren, Y.C.[Yu-Chen], Mao, Z.D.[Zhen-Dong], Fang, S.C.[Shan-Cheng], Lu, Y.[Yan], He, T.[Tong], Du, H.[Hao], Zhang, Y.D.[Yong-Dong], Ouyang, W.L.[Wan-Li],
Crossing the Gap: Domain Generalization for Image Captioning,
CVPR23(2871-2880)
IEEE DOI 2309
BibRef

Liu, Y.C.[Yu-Chen], Wang, Y.M.[Yao-Ming], Chen, Y.[Yabo], Dai, W.R.[Wen-Rui], Li, C.L.[Cheng-Lin], Zou, J.[Junni], Xiong, H.K.[Hong-Kai],
Promoting Semantic Connectivity: Dual Nearest Neighbors Contrastive Learning for Unsupervised Domain Generalization,
CVPR23(3510-3519)
IEEE DOI 2309
BibRef

Chung, W.H.[Wei-Hao], Hsieh, C.J.[Cheng-Ju], Liu, S.H.[Sheng-Hung], Hsu, C.T.[Chiou-Ting],
Domain Generalized RPPG Network: Disentangled Feature Learning with Domain Permutation and Domain Augmentation,
ACCV22(II:41-57).
Springer DOI 2307
BibRef

Sultana, M.[Maryam], Naseer, M.[Muzammal], Khan, M.H.[Muhammad Haris], Khan, S.[Salman], Khan, F.S.[Fahad Shahbaz],
Self-distilled Vision Transformer for Domain Generalization,
ACCV22(II:273-290).
Springer DOI 2307
BibRef

Mondal, B.[Biswajit], Biswas, S.[Soma],
SEIC: Semantic Embedding with Intermediate Classes for Zero-shot Domain Generalization,
ACCV22(V:333-350).
Springer DOI 2307
BibRef

Li, A.[Aodi], Zhuang, L.S.[Lian-Sheng], Fan, S.[Shuo], Wang, S.[Shafei],
Learning Common and Specific Visual Prompts for Domain Generalization,
ACCV22(VI:578-593).
Springer DOI 2307
BibRef

Garrido-Munoz, C.[Carlos], Alfaro-Contreras, M.[María], Calvo-Zaragoza, J.[Jorge],
Evaluating Domain Generalization in Kitchen Utensils Classification,
IbPRIA23(108-118).
Springer DOI 2307
BibRef

Chen, H.R.[Huan-Ran], Shao, S.T.[Shi-Tong], Wang, Z.[Ziyi], Shang, Z.[Zirui], Chen, J.[Jin], Ji, X.F.[Xiao-Feng], Wu, X.X.[Xin-Xiao],
Bootstrap Generalization Ability from Loss Landscape Perspective,
CiV22(500-517).
Springer DOI 2304
BibRef

Bajcsy, P.[Peter], Majurski, M.[Michael], Cleveland IV, T.E.[Thomas E.], Carrasco, M.[Manuel], Keyrouz, W.[Walid],
Characterization of AI Model Configurations for Model Reuse,
BioImage22(454-469).
Springer DOI 2304
BibRef

Jiang, Y.X.[Yu-Xuan], Wang, Y.F.[Yan-Feng], Zhang, R.P.[Rui-Peng], Xu, Q.[Qinwei], Zhang, Y.[Ya], Chen, X.[Xin], Tian, Q.[Qi],
Domain-conditioned Normalization for Test-time Domain Generalization,
OutDistri22(291-307).
Springer DOI 2304
BibRef

Marinov, Z.[Zdravko], Roitberg, A.[Alina], Schneider, D.[David], Stiefelhagen, R.[Rainer],
Modselect: Automatic Modality Selection for Synthetic-to-real Domain Generalization,
OutDistri22(326-346).
Springer DOI 2304
BibRef

Lu, Y.[Yulei], Luo, Y.[Yawei], Pan, A.[Antao], Mao, Y.J.[Yang-Jun], Xiao, J.[Jun],
Domain Generalization with Global Sample Mixup,
CiV22(518-529).
Springer DOI 2304
BibRef

Lv, Z.[Zhi], Lin, B.[Bo], Liang, S.Y.[Si-Yuan], Wang, L.H.[Li-Hua], Yu, M.[Mochen], Tang, Y.[Yao], Liang, J.J.[Jia-Jun],
Simpledg: Simple Domain Generalization Baseline Without Bells and Whistles,
CiV22(477-487).
Springer DOI 2304
BibRef

O'Brien, M.[Molly], Wolfinger, B.[Brett], Bukowski, J.[Julia], Unberath, M.[Mathias], Pezeshk, A.[Aria], Hager, G.[Greg],
Mapping DNN Embedding Manifolds for Network Generalization Prediction,
WACV23(6513-6522)
IEEE DOI 2302
Manifolds, Visualization, Image analysis, Melanoma, Metadata, Applications: Robotics, Biomedical/healthcare/medicine BibRef

Chen, T.[Tianle], Baktashmotlagh, M.[Mahsa], Wang, Z.J.[Zi-Jian], Salzmann, M.[Mathieu],
Center-aware Adversarial Augmentation for Single Domain Generalization,
WACV23(4146-4154)
IEEE DOI 2302
Training, Perturbation methods, Semantics, Training data, Benchmark testing, Feature extraction, and algorithms (including transfer) BibRef

Gokhale, T.[Tejas], Anirudh, R.[Rushil], Thiagarajan, J.J.[Jayaraman J.], Kailkhura, B.[Bhavya], Baral, C.[Chitta], Yang, Y.Z.[Ye-Zhou],
Improving Diversity with Adversarially Learned Transformations for Domain Generalization,
WACV23(434-443)
IEEE DOI 2302
Training, Perturbation methods, Neural networks, Transforms, Benchmark testing, Performance gain, and algorithms (including transfer) BibRef

Chen, J.M.[Jun-Ming], Jiang, M.[Meirui], Dou, Q.[Qi], Chen, Q.F.[Qi-Feng],
Federated Domain Generalization for Image Recognition via Cross-Client Style Transfer,
WACV23(361-370)
IEEE DOI 2302
Training, Data privacy, Image recognition, Federated learning, Data models, Picture archiving and communication systems, ethical computer vision BibRef

Nguyen, T.[Thuan], Lyu, B.Y.[Bo-Yang], Ishwar, P.[Prakash], Scheutz, M.[Matthias], Aeron, S.[Shuchin],
Conditional entropy minimization principle for learning domain invariant representation features,
ICPR22(3000-3006)
IEEE DOI 2212
Mixture models, Filtering algorithms, Minimization, Feature extraction, Entropy, Filtering theory, Classification algorithms BibRef

Liu, X.X.[Xi-Xi], Staudt, D., Lin, C.T.[Che-Tsung], Zach, C.[Christopher],
Effortless Training of Joint Energy-Based Models with Sliced Score Matching,
ICPR22(2643-2649)
IEEE DOI 2212
Training, Analytical models, Uncertainty, Stochastic processes, Predictive models, Logic gates, Calibration BibRef

Tao, C.F.[Chao-Fan], Wong, N.[Ngai],
ODG-Q: Robust Quantization via Online Domain Generalization,
ICPR22(1822-1828)
IEEE DOI 2212
Training, Quantization (signal), Costs, Perturbation methods, Neural networks, Closed box, Robustness BibRef

Frikha, A.[Ahmed], Krompaß, D.[Denis], Tresp, V.[Volker],
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption,
ICPR22(1871-187)
IEEE DOI 2212
Training, Machine learning, Benchmark testing, Data models BibRef

Zhang, W.Y.[Wen-Yu], Ragab, M.[Mohamed], Foo, C.S.[Chuan-Sheng],
Domain Generalization via Selective Consistency Regularization for Time Series Classification,
ICPR22(2149-2156)
IEEE DOI 2212
Representation learning, Training, Time series analysis, Feature extraction, Data models, Calibration BibRef

Chen, T.L.[Tian-Le], Baktashmotlagh, M.[Mahsa], Salzmann, M.[Mathieu],
Contrastive Class-aware Adaptation for Domain Generalization,
ICPR22(4871-4876)
IEEE DOI 2212
Training, Heart, Semantic segmentation, Semantics, Predictive models, Feature extraction, Market research 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

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

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.B.[Yan-Bei], 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.H.[Hao-Han], 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.S.[Rogerio S.], 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.C.[Jiong-Cheng], 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.H.[Ming-Han], Li, R.H.[Rui-Huang], 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.T.[Zi-Teng], 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.H.[Rui-Hong], 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

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], Yang, F.[Feng], Gong, B.Q.[Bo-Qing], Zhou, M.Y.[Ming-Yuan],
Adversarially Adaptive Normalization for Single Domain Generalization,
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 BibRef

Mitsuzumi, Y.[Yu], Irie, G.[Go], Ikami, D.[Daiki], Shibata, T.[Takashi],
Generalized Domain Adaptation,
CVPR21(1084-1093)
IEEE DOI 2111
Benchmark testing, Pattern recognition BibRef

Li, L.[Lei], Gao, K.[Ke], Cao, J.[Juan], Huang, Z.Y.[Zi-Yao], Weng, Y.P.[Ye-Peng], Mi, X.Y.[Xiao-Yue], Yu, Z.Z.[Zheng-Ze], Li, X.Y.[Xiao-Ya], Xia, B.Y.[Bo-Yang],
Progressive Domain Expansion Network for Single Domain Generalization,
CVPR21(224-233)
IEEE DOI 2111
Training, Handheld computers, Computational modeling, Semantics, Transforms, Performance gain, Generators BibRef

Eguchi, S.[Shu], Nakamura, R.[Ryo], Tanaka, M.[Masaru],
Output augmentation works well without any domain knowledge,
MVA21(1-5)
DOI Link 2109
To improve generalization performance, without requiring data augmentation. Training data, Task analysis, Image classification BibRef

Borlino, F.C.[Francesco Cappio], d'Innocente, A.[Antonio], Tommasi, T.[Tatiana],
Rethinking Domain Generalization Baselines,
ICPR21(9227-9233)
IEEE DOI 2105
Deep learning, Writing, Tools, Robustness, Data models, Pattern recognition, Standards BibRef

Wang, Z.Q.[Zi-Qi], Loog, M.[Marco], van Gemert, J.C.[Jan C.],
Respecting Domain Relations: Hypothesis Invariance for Domain Generalization,
ICPR21(9756-9763)
IEEE DOI 2105
Training, Estimation, Distributed databases, Probabilistic logic, Pattern recognition, Reliability, Domain generalization, invariant representation BibRef

Seo, S.[Seonguk], Suh, Y.[Yumin], Kim, D.W.[Dong-Wan], Kim, G.[Geeho], Han, J.W.[Jong-Woo], Han, B.H.[Bo-Hyung],
Learning to Optimize Domain Specific Normalization for Domain Generalization,
ECCV20(XXII:68-83).
Springer DOI 2011
BibRef

Chattopadhyay, P.[Prithvijit], Balaji, Y.[Yogesh], Hoffman, J.[Judy],
Learning to Balance Specificity and Invariance for In and Out of Domain Generalization,
ECCV20(IX:301-318).
Springer DOI 2011
BibRef

Wang, S.J.[Shu-Jun], Yu, L.[Lequan], Li, C.[Caizi], Fu, C.W.[Chi-Wing], Heng, P.A.[Pheng-Ann],
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization,
ECCV20(IX:159-176).
Springer DOI 2011
BibRef

Qiao, F., Zhao, L., Peng, X.,
Learning to Learn Single Domain Generalization,
CVPR20(12553-12562)
IEEE DOI 2008
Training, Task analysis, Transportation, Adaptation models, Robustness, Perturbation methods, Measurement BibRef

Truong, D.T.[Dat T.], Duong, C.N.[Chi Nhan], Luu, K.[Khoa], Tran, M.T.[Minh-Triet], Le, N.[Ngan],
Domain Generalization via Universal Non-volume Preserving Approach,
CRV20(93-100)
IEEE DOI 2006
Digits, faces, pedestrians. BibRef

Yue, X., Zhang, Y., Zhao, S., Sangiovanni-Vincentelli, A., Keutzer, K., Gong, B.,
Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data,
ICCV19(2100-2110)
IEEE DOI 2004
feature extraction, image representation, image segmentation, learning (artificial intelligence), Adaptation models BibRef

Li, D., Zhang, J., Yang, Y., Liu, C., Song, Y., Hospedales, T.M.,
Episodic Training for Domain Generalization,
ICCV19(1446-1455)
IEEE DOI 2004
convolutional neural nets, feature extraction, generalisation (artificial intelligence), Data models BibRef

d'Innocente, A.[Antonio], Caputo, B.[Barbara],
Domain Generalization with Domain-Specific Aggregation Modules,
GCPR18(187-198).
Springer DOI 1905
BibRef

Motiian, S., Piccirilli, M., Adjeroh, D.A., Doretto, G.,
Unified Deep Supervised Domain Adaptation and Generalization,
ICCV17(5716-5726)
IEEE DOI 1802
feature extraction, image representation, learning (artificial intelligence), statistical distributions, Visualization BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multi-Task Learning, Multiple Tasks, Transfer Learning, Domain Adaption .


Last update:Jun 5, 2024 at 10:22:22