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 1551–1575 of 6439 papers

Title	Date	Tasks	Status	Score
Improving Pseudo Labels With Intra-Class Similarity for Unsupervised Domain Adaptation	Jul 25, 2022	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	5
DAME: Domain Adaptation for Matching Entities	Apr 20, 2022	Domain AdaptationZero-Shot Learning	CodeCode Available	5
Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation	Aug 12, 2019	Domain AdaptationMRI segmentation	CodeCode Available	5
Learning from a Complementary-label Source Domain: Theory and Algorithms	Aug 4, 2020	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	5
Improving Span Representation for Domain-adapted Coreference Resolution	Sep 20, 2021	coreference-resolutionCoreference Resolution	CodeCode Available	5
Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning	Oct 18, 2021	DiagnosticDomain Adaptation	CodeCode Available	5
Improving land cover segmentation across satellites using domain adaptation	Nov 25, 2019	Domain AdaptationEarth Observation	CodeCode Available	5
Improving Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models	Dec 7, 2023	Domain AdaptationMedical Report Generation	CodeCode Available	5
Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels	Aug 7, 2023	Domain AdaptationDomain Generalization	CodeCode Available	5
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing	Jan 17, 2019	Domain AdaptationFace Anti-Spoofing	CodeCode Available	5
DALLMi: Domain Adaption for LLM-based Multi-label Classifier	May 3, 2024	Domain AdaptationLanguage Modeling	CodeCode Available	5
DALI: Domain Adaptive LiDAR Object Detection via Distribution-level and Instance-level Pseudo Label Denoising	Dec 11, 2024	DenoisingDomain Adaptation	CodeCode Available	5
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models	Jun 6, 2024	Domain Adaptation	CodeCode Available	5
Improving Document Binarization via Adversarial Noise-Texture Augmentation	Oct 25, 2018	Adversarial RobustnessBinarization	CodeCode Available	5
Improving Both Domain Robustness and Domain Adaptability in Machine Translation	Dec 15, 2021	Domain AdaptationMachine Translation	CodeCode Available	5
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations	Aug 27, 2024	Adversarial RobustnessAndroid Malware Detection	CodeCode Available	5
Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant Features	Feb 4, 2025	3D Object DetectionAutonomous Driving	CodeCode Available	5
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-Translation	Nov 1, 2019	Data AugmentationDiversity	CodeCode Available	5
Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings	Aug 1, 2019	Active LearningDomain Adaptation	CodeCode Available	5
Implicit Semantic Response Alignment for Partial Domain Adaptation	Dec 1, 2021	Domain AdaptationPartial Domain Adaptation	CodeCode Available	5
IMPaSh: A Novel Domain-shift Resistant Representation for Colorectal Cancer Tissue Classification	Aug 23, 2022	Contrastive LearningDomain Adaptation	CodeCode Available	5
DAD++: Improved Data-free Test Time Adversarial Defense	Sep 10, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation	Jan 15, 2025	Domain AdaptationDomain Generalization	CodeCode Available	5
Deep Domain Adaptation for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labelled Videos	Aug 13, 2020	Depression DetectionDomain Adaptation	CodeCode Available	5
Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift	Nov 29, 2020	Domain AdaptationGeneralization Bounds	CodeCode Available	5

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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