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 1601–1625 of 6439 papers

Title	Date	Tasks	Status	Score
Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant Features	Feb 4, 2025	3D Object DetectionAutonomous Driving	CodeCode Available	5
Improving land cover segmentation across satellites using domain adaptation	Nov 25, 2019	Domain AdaptationEarth Observation	CodeCode Available	5
Improving Both Domain Robustness and Domain Adaptability in Machine Translation	Dec 15, 2021	Domain AdaptationMachine Translation	CodeCode Available	5
Bandit Structured Prediction for Neural Sequence-to-Sequence Learning	Apr 21, 2017	Domain AdaptationMachine Translation	CodeCode Available	5
Improving Document Binarization via Adversarial Noise-Texture Augmentation	Oct 25, 2018	Adversarial RobustnessBinarization	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 Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models	Dec 7, 2023	Domain AdaptationMedical Report Generation	CodeCode Available	5
Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR	Mar 3, 2017	compressed sensingComputed Tomography (CT)	CodeCode Available	5
Deep Least Squares Alignment for Unsupervised Domain Adaptation	Nov 3, 2021	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	5
Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation	Oct 6, 2022	Domain AdaptationLanguage Modeling	CodeCode Available	5
Interactive Learning for Semantic Segmentation in Earth Observation	Sep 23, 2020	Domain AdaptationEarth Observation	CodeCode Available	5
D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment	Jan 10, 2024	ClassificationDomain Adaptation	CodeCode Available	5
Implicit Semantic Response Alignment for Partial Domain Adaptation	Dec 1, 2021	Domain AdaptationPartial Domain Adaptation	CodeCode Available	5
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image Classification	Oct 30, 2019	Domain AdaptationFew-Shot Image Classification	CodeCode Available	5
Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift	Nov 29, 2020	Domain AdaptationGeneralization Bounds	CodeCode Available	5
Impact of ImageNet Model Selection on Domain Adaptation	Feb 6, 2020	BenchmarkingDomain Adaptation	CodeCode Available	5
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification	Nov 19, 2017	Domain AdaptationGenerative Adversarial Network	CodeCode Available	5
Adaptive Deep Learning through Visual Domain Localization	Feb 24, 2018	Deep LearningDomain 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
Improve Cross-domain Mixed Sampling with Guidance Training for Adaptive Segmentation	Mar 22, 2024	Domain AdaptationPseudo Label	CodeCode Available	5
Cycle-consistent Conditional Adversarial Transfer Networks	Sep 17, 2019	Domain AdaptationTransfer Learning	CodeCode Available	5
Deep Residual Correction Network for Partial Domain Adaptation	Apr 10, 2020	Domain AdaptationPartial Domain Adaptation	CodeCode Available	5
Cycle-Balanced Representation Learning For Counterfactual Inference	Oct 29, 2021	counterfactualCounterfactual Inference	CodeCode Available	5
CycDA: Unsupervised Cycle Domain Adaptation from Image to Video	Mar 30, 2022	Action RecognitionDomain Adaptation	CodeCode Available	5
ILGNet: Inception Modules with Connected Local and Global Features for Efficient Image Aesthetic Quality Classification using Domain Adaptation	Oct 7, 2016	Aesthetics Quality AssessmentDomain Adaptation	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