Domain Adaptation

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1501–1525 of 6439 papers

Title	Date	Tasks	Status
A Brief Review of Domain Adaptation	Oct 7, 2020	BIG-bench Machine LearningDomain Adaptation	—Unverified
Domain Adaptation for Disease Phrase Matching with Adversarial Networks	Jul 1, 2018	Domain AdaptationEntity Linking	—Unverified
Domain Adaptation for Learning Generator from Paired Few-Shot Data	Feb 25, 2021	DiversityDomain Adaptation	—Unverified
A Multilingual BPE Embedding Space for Universal Sentiment Lexicon Induction	Jul 1, 2019	DiversityDomain Adaptation	—Unverified
BOUN at SemEval-2021 Task 9: Text Augmentation Techniques for Fact Verification in Tabular Data	Aug 1, 2021	Domain AdaptationFact Verification	—Unverified
Domain Adaptation by Mixture of Alignments of Second- or Higher-Order Scatter Tensors	Nov 24, 2016	Domain Adaptation	—Unverified
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding	Dec 1, 2021	DisentanglementDomain Adaptation	—Unverified
A Multi-Domain Translation Model Framework for Statistical Machine Translation	Aug 1, 2013	Domain AdaptationMachine Translation	—Unverified
Domain Adaptation by Topology Regularization	Jan 28, 2021	Domain AdaptationTopological Data Analysis	—Unverified
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation	Mar 25, 2023	Domain AdaptationERP	—Unverified
A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation	Mar 27, 2018	Domain AdaptationGenerative Adversarial Network	—Unverified
Active Semantic Localization with Graph Neural Embedding	May 10, 2023	CPUDomain Adaptation	—Unverified
Boosting Unsupervised Domain Adaptation with Soft Pseudo-label and Curriculum Learning	Dec 3, 2021	Domain AdaptationPseudo Label	—Unverified
Boosting Supervised Learning Performance with Co-training	Nov 18, 2021	Domain Adaptationobject-detection	—Unverified
Domain Adaptation by Maximizing Population Correlation with Neural Architecture Search	Sep 12, 2021	Domain AdaptationNeural Architecture Search	—Unverified
Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words	Nov 1, 2020	Domain AdaptationWord Embeddings	—Unverified
Self-Paced Learning for Open-Set Domain Adaptation	Mar 10, 2023	Domain Adaptation	—Unverified
Amplitude Spectrum Transformation for Open Compound Domain Adaptive Semantic Segmentation	Feb 9, 2022	DisentanglementDomain Adaptation	—Unverified
Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All-in-One Classifier	Nov 21, 2022	AllContrastive Learning	—Unverified
Abductive Reasoning as Self-Supervision for Common Sense Question Answering	Sep 6, 2019	Common Sense ReasoningDomain Adaptation	—Unverified
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions	Nov 17, 2020	Domain AdaptationEmotion Classification	—Unverified
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies	Feb 16, 2021	Domain AdaptationQuestion Answering	—Unverified
AMM: Adaptive Modularized Reinforcement Model for Multi-city Traffic Signal Control	Jan 5, 2025	Domain AdaptationMeta-Learning	—Unverified
Domain Adaptation-based Edge Computing for Cross-Conditions Fault Diagnosis	Nov 15, 2024	DiagnosticDomain Adaptation	—Unverified
Boosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation	May 11, 2025	Autonomous DrivingDomain Adaptation	—Unverified

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All datasets Office-31 SYNTHIA-to-Cityscapes GTA5 to Cityscapes Office-Home VisDA2017 ImageCLEF-DA Cityscapes to ACDC MNIST-to-USPS SVHN-to-MNIST USPS-to-MNIST SVNH-to-MNIST MoLane

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Average Accuracy	96	—	Unverified
2	PMTrans	Average Accuracy	95.3	—	Unverified
3	CMKD	Average Accuracy	94.4	—	Unverified
4	SSRT-B (ours)	Average Accuracy	93.5	—	Unverified
5	CDTrans	Average Accuracy	92.6	—	Unverified
6	CoVi	Average Accuracy	91.8	—	Unverified
7	GSDE	Average Accuracy	91.7	—	Unverified
8	FixBi	Average Accuracy	91.4	—	Unverified
9	Contrastive Adaptation Network	Average Accuracy	90.6	—	Unverified
10	BIWAA	Average Accuracy	90.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	78.1	—	Unverified
2	ILM-ASSL	mIoU	76.6	—	Unverified
3	DCF	mIoU	69.3	—	Unverified
4	HRDA+PiPa	mIoU	68.2	—	Unverified
5	MIC	mIoU	67.3	—	Unverified
6	FREDOM - Transformer	mIoU	67	—	Unverified
7	HRDA	mIoU	65.8	—	Unverified
8	SePiCo	mIoU	64.3	—	Unverified
9	MIC + Guidance Training	mIoU	63.8	—	Unverified
10	DAFormer + ProCST	mIoU	61.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HALO	mIoU	77.8	—	Unverified
2	DCF	mIoU	77.7	—	Unverified
3	ILM-ASSL	mIoU	76.1	—	Unverified
4	MIC	mIoU	75.9	—	Unverified
5	HRDA+PiPa	mIoU	75.6	—	Unverified
6	HRDA	mIoU	73.8	—	Unverified
7	FREDOM - Transformer	mIoU	73.6	—	Unverified
8	HALO	mIoU	73.3	—	Unverified
9	SePiCo	mIoU	70.3	—	Unverified
10	DAFormer + ProCST	mIoU	69.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SWG	Accuracy	92.3	—	Unverified
2	RCL	Accuracy	90	—	Unverified
3	PGA (ViT-L/14)	Accuracy	89.4	—	Unverified
4	PMTrans	Accuracy	89	—	Unverified
5	CMKD	Accuracy	89	—	Unverified
6	MIC	Accuracy	86.2	—	Unverified
7	PGA (ViT-B/16)	Accuracy	85.1	—	Unverified
8	ELS	Accuracy	84.6	—	Unverified
9	SDAT (ViT-B/16)	Accuracy	84.3	—	Unverified
10	CDTrans (DeiT-B)	Accuracy	80.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FFTAT	Accuracy	93.8	—	Unverified
2	RCL	Accuracy	93.2	—	Unverified
3	MIC	Accuracy	92.8	—	Unverified
4	SWG	Accuracy	92.7	—	Unverified
5	CMKD	Accuracy	91.8	—	Unverified
6	DePT	Accuracy	90.7	—	Unverified
7	SDAT(ViT)	Accuracy	89.8	—	Unverified
8	SFDA2++	Accuracy	89.6	—	Unverified
9	PMtrans	Accuracy	88.8	—	Unverified
10	CoVi	Accuracy	88.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CMKD	Accuracy	94.3	—	Unverified
2	MCC+NWD	Accuracy	90.7	—	Unverified
3	GLOT-DR	Accuracy	90.4	—	Unverified
4	SPL	Accuracy	90.3	—	Unverified
5	DFA-SAFN	Accuracy	90.2	—	Unverified
6	DADA	Accuracy	89.3	—	Unverified
7	DFA-ENT	Accuracy	89.1	—	Unverified
8	MEDM	Accuracy	88.9	—	Unverified
9	DDA	Accuracy	88.9	—	Unverified
10	IAFN+ENT	Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoRA	mIoU	78.8	—	Unverified
2	Rein	mIoU	77.6	—	Unverified
3	CoDA	mIoU	72.6	—	Unverified
4	Refign (HRDA)	mIoU	72.1	—	Unverified
5	HALO	mIoU	71.9	—	Unverified
6	MIC	mIoU	70.4	—	Unverified
7	HRDA	mIoU	68	—	Unverified
8	Refign (DAFormer)	mIoU	65.5	—	Unverified
9	VBLC (DAFormer)	mIoU	64.2	—	Unverified
10	CMFormer	mIoU	60.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FACT	Accuracy	98.8	—	Unverified
2	FAMCD	Accuracy	98.72	—	Unverified
3	DFA-MCD	Accuracy	98.6	—	Unverified
4	Mean teacher	Accuracy	98.26	—	Unverified
5	DRANet	Accuracy	98.2	—	Unverified
6	SHOT	Accuracy	98	—	Unverified
7	DFA-ENT	Accuracy	97.9	—	Unverified
8	CyCleGAN (Light-weight Calibrator)	Accuracy	97.1	—	Unverified