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 4751–4775 of 6439 papers

Title	Date	Tasks	Status
Measuring the Feasibility of Analogical Transfer using Complexity	Jun 23, 2022	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
MedAI at SemEval-2021 Task 10: Negation-aware Pre-training for Source-free Negation Detection Domain Adaptation	Aug 1, 2021	Domain AdaptationNegation	—Unverified
MedFLIP: Medical Vision-and-Language Self-supervised Fast Pre-Training with Masked Autoencoder	Mar 7, 2024	Domain AdaptationMedical Image Analysis	—Unverified
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment	Aug 18, 2024	Brain Tumor SegmentationDomain Adaptation	—Unverified
MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection	Mar 7, 2021	Domain Adaptationobject-detection	—Unverified
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation	Oct 9, 2023	Domain AdaptationUniversal Domain Adaptation	—Unverified
Memory Consistent Unsupervised Off-the-Shelf Model Adaptation for Source-Relaxed Medical Image Segmentation	Sep 16, 2022	Brain Tumor SegmentationDomain Adaptation	—Unverified
Memory Efficient Temporal & Visual Graph Model for Unsupervised Video Domain Adaptation	Aug 13, 2022	Domain AdaptationGraph Attention	—Unverified
Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation	May 11, 2023	Cardiac SegmentationDomain Adaptation	—Unverified
Meta-Learned Feature Critics for Domain Generalized Semantic Segmentation	Dec 27, 2021	DisentanglementDomain Adaptation	—Unverified
Meta-Learning across Meta-Tasks for Few-Shot Learning	Feb 11, 2020	Domain AdaptationFew-Shot Learning	—Unverified
Meta-Learning for Few-Shot NMT Adaptation	Apr 6, 2020	Domain AdaptationMachine Translation	—Unverified
Meta-Learning with Domain Adaptation for Few-Shot Learning under Domain Shift	May 1, 2019	Domain AdaptationFew-Shot Learning	—Unverified
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning	Aug 27, 2019	Data AugmentationDomain Adaptation	—Unverified
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions	Jan 4, 2024	Domain AdaptationTest-time Adaptation	—Unverified
Meta-Reinforced Multi-Domain State Generator for Dialogue Systems	Jul 1, 2020	Domain AdaptationMeta-Learning	—Unverified
Meta Reinforcement Learning for Sim-to-real Domain Adaptation	Sep 16, 2019	Domain AdaptationMeta-Learning	—Unverified
MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation	Apr 17, 2025	DiversityDomain Adaptation	—Unverified
Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification	Aug 4, 2023	Domain AdaptationMeta-Learning	—Unverified
Meta-TTT: A Meta-learning Minimax Framework For Test-Time Training	Oct 2, 2024	DiversityDomain Adaptation	—Unverified
Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning	Oct 7, 2021	Domain AdaptationMeta-Learning	—Unverified
Metric-Learning-Assisted Domain Adaptation	Apr 23, 2020	Domain AdaptationMetric Learning	—Unverified
Metric Learning for Graph-Based Domain Adaptation	Dec 1, 2012	Domain AdaptationMetric Learning	—Unverified
MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation	Jan 1, 2023	Active LearningDomain Adaptation	—Unverified
MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint	Jul 22, 2020	Domain AdaptationGenerative Adversarial Network	—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