Domain Generalization

The idea of Domain Generalization is to learn from one or multiple training domains, to extract a domain-agnostic model which can be applied to an unseen domain

Source: Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 501–525 of 1751 papers

Title	Date	Tasks	Status	Hype
Natural Adversarial Examples	Jul 16, 2019	Adversarial AttackData Augmentation	CodeCode Available	1
Invariant Risk Minimization	Jul 5, 2019	Domain GeneralizationImage Classification	CodeCode Available	1
Learning Robust Global Representations by Penalizing Local Predictive Power	May 29, 2019	Domain AdaptationDomain Generalization	CodeCode Available	1
DIVA: Domain Invariant Variational Autoencoders	May 24, 2019	Domain GeneralizationRotated MNIST	CodeCode Available	1
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features	May 13, 2019	Domain GeneralizationImage Captioning	CodeCode Available	1
Adversarial Training for Free!	Apr 29, 2019	Adversarial AttackAdversarial Defense	CodeCode Available	1
Making Convolutional Networks Shift-Invariant Again	Apr 25, 2019	Classification ConsistencyConditional Image Generation	CodeCode Available	1
A Closer Look at Few-shot Classification	Apr 8, 2019	Domain GeneralizationFew-Shot Learning	CodeCode Available	1
Bag of Tricks for Image Classification with Convolutional Neural Networks	Dec 4, 2018	Domain GeneralizationGeneral Classification	CodeCode Available	1
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness	Nov 29, 2018	Domain GeneralizationImage Classification	CodeCode Available	1
Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net	Jul 25, 2018	All-day Semantic SegmentationDomain Adaptation	CodeCode Available	1
mixup: Beyond Empirical Risk Minimization	Oct 25, 2017	Domain GeneralizationImage Classification	CodeCode Available	1
Learning to Generalize: Meta-Learning for Domain Generalization	Oct 10, 2017	Domain Generalizationimage-classification	CodeCode Available	1
Deeper, Broader and Artier Domain Generalization	Oct 9, 2017	Domain Generalization	CodeCode Available	1
Improved Regularization of Convolutional Neural Networks with Cutout	Aug 15, 2017	Data AugmentationDomain Generalization	CodeCode Available	1
Aggregated Residual Transformations for Deep Neural Networks	Nov 16, 2016	Domain GeneralizationGeneral Classification	CodeCode Available	1
Deep CORAL: Correlation Alignment for Deep Domain Adaptation	Jul 6, 2016	Domain AdaptationDomain Generalization	CodeCode Available	1
Domain Generalization for Object Recognition with Multi-task Autoencoders	Aug 31, 2015	DenoisingDomain Generalization	CodeCode Available	1
Domain-Adversarial Training of Neural Networks	May 28, 2015	Domain AdaptationDomain Generalization	CodeCode Available	1
Very Deep Convolutional Networks for Large-Scale Image Recognition	Sep 4, 2014	Activity Recognition In VideosClassification	CodeCode Available	1
Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization	Jul 17, 2025	Domain GeneralizationEnsemble Learning	CodeCode Available	0
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling	Jul 17, 2025	Domain GeneralizationImputation	—Unverified	0
GLAD: Generalizable Tuning for Vision-Language Models	Jul 17, 2025	Domain GeneralizationFew-Shot Learning	—Unverified	0
From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion	Jul 11, 2025	Domain GeneralizationUncertainty Quantification	—Unverified	0
Integrated Structural Prompt Learning for Vision-Language Models	Jul 8, 2025	Domain GeneralizationPrompt Learning	—Unverified	0

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All datasets PACS VizWiz-Classification ImageNet-C Office-Home ImageNet-A ImageNet-R DomainNet VLCS TerraIncognita GTA-to-Avg(Cityscapes,BDD,Mapillary)ImageNet-Sketch GTA5 to Cityscapes

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SIMPLE+	Average Accuracy	99	—	Unverified
2	PromptStyler (CLIP, ViT-L/14)	Average Accuracy	98.6	—	Unverified
3	GMDG (RegNetY-16GF, SWAD)	Average Accuracy	97.9	—	Unverified
4	D-Triplet(RegNetY-16GF)	Average Accuracy	97.6	—	Unverified
5	MoA (OpenCLIP, ViT-B/16)	Average Accuracy	97.4	—	Unverified
6	GMDG (e RegNetY-16GF)	Average Accuracy	97.3	—	Unverified
7	PromptStyler (CLIP, ViT-B/16)	Average Accuracy	97.2	—	Unverified
8	SPG (CLIP, ViT-B/16)	Average Accuracy	97	—	Unverified
9	CAR-FT (CLIP, ViT-B/16)	Average Accuracy	96.8	—	Unverified
10	MIRO (RegNetY-16GF, SWAD)	Average Accuracy	96.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViT-8/B-224	Accuracy - Clean Images	450	—	Unverified
2	VOLO-D5	Accuracy - All Images	57.2	—	Unverified
3	ConvNeXt-B	Accuracy - All Images	53.5	—	Unverified
4	ResNeXt-101 32x16d	Accuracy - All Images	51.7	—	Unverified
5	EfficientNet-B8 (advprop+autoaug)	Accuracy - All Images	50.5	—	Unverified
6	EfficientNet-B7 (advprop+autoaug)	Accuracy - All Images	49.7	—	Unverified
7	EfficientNet-B6 (advprop+autoaug)	Accuracy - All Images	49.6	—	Unverified
8	EfficientNet-B5 (advprop+autoaug)	Accuracy - All Images	49.1	—	Unverified
9	ViT-16/L-224	Accuracy - All Images	49	—	Unverified
10	ResNet-50 (gn)	Accuracy - All Images	48.9	—	Unverified