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 4651–4675 of 6439 papers

Title	Date	Tasks	Status
Le corpus Sequoia : annotation syntaxique et exploitation pour l'adaptation d'analyseur par pont lexical (The Sequoia Corpus : Syntactic Annotation and Use for a Parser Lexical Domain Adaptation Method) [in French]	Jun 1, 2012	Domain Adaptation	—Unverified
Length of Stay prediction for Hospital Management using Domain Adaptation	Jun 29, 2023	Domain AdaptationLength-of-Stay prediction	—Unverified
LENS: Localization enhanced by NeRF synthesis	Oct 13, 2021	3D geometryData Augmentation	—Unverified
Less-forgetful Learning for Domain Expansion in Deep Neural Networks	Nov 16, 2017	Domain Adaptationimage-classification	—Unverified
Let Synthetic Data Shine: Domain Reassembly and Soft-Fusion for Single Domain Generalization	Mar 17, 2025	Domain AdaptationDomain Generalization	—Unverified
Leveraging 2D Masked Reconstruction for Domain Adaptation of 3D Pose Estimation	Jan 14, 2025	3D Pose EstimationDomain Adaptation	—Unverified
Leveraging Auxiliary Tasks for Document-Level Cross-Domain Sentiment Classification	Nov 1, 2017	ClassificationDenoising	—Unverified
Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift	Dec 2, 2019	Domain AdaptationSemantic Shift Detection	—Unverified
Leveraging Contrastive Learning for Semantic Segmentation with Consistent Labels Across Varying Appearances	Dec 21, 2024	Contrastive LearningDomain Adaptation	—Unverified
Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery	May 4, 2019	Data AugmentationDomain Adaptation	—Unverified
Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts	Jul 5, 2024	Active LearningDomain Adaptation	—Unverified
Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic	Dec 5, 2023	Data AugmentationDomain Adaptation	—Unverified
Leveraging Domain Adaptation for Low-Resource Geospatial Machine Learning	Jul 11, 2021	BIG-bench Machine LearningDomain Adaptation	—Unverified
Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models	May 26, 2025	Domain AdaptationInstruction Following	—Unverified
Leveraging Motion Priors in Videos for Improving Human Segmentation	Jul 30, 2018	Active LearningDomain Adaptation	—Unverified
Leveraging Multiple Domains for Sentiment Classification	Dec 1, 2016	ClassificationDomain Adaptation	—Unverified
Leveraging over intact priors for boosting control and dexterity of prosthetic hands by amputees	Aug 26, 2016	Domain Adaptation	—Unverified
FogAdapt: Self-Supervised Domain Adaptation for Semantic Segmentation of Foggy Images	Jan 7, 2022	Domain AdaptationFoggy Scene Segmentation	—Unverified
Leveraging Speaker Embeddings with Adversarial Multi-task Learning for Age Group Classification	Jan 22, 2023	Domain AdaptationMulti-Task Learning	—Unverified
Leveraging Synthetic Data for Generalizable and Fair Facial Action Unit Detection	Mar 15, 2024	Action Unit DetectionDomain Adaptation	—Unverified
Leveraging the Domain Adaptation of Retrieval Augmented Generation Models for Question Answering and Reducing Hallucination	Oct 23, 2024	Domain AdaptationHallucination	—Unverified
Leveraging Topology for Domain Adaptive Road Segmentation in Satellite and Aerial Imagery	Sep 27, 2023	Autonomous VehiclesDomain Adaptation	—Unverified
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching	Oct 13, 2020	Domain AdaptationSemi-Supervised Image Classification	—Unverified
LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation	Mar 2, 2020	DiversityDomain Adaptation	—Unverified
Lidar Upsampling with Sliced Wasserstein Distance	Jan 31, 2023	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