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 2576–2600 of 6439 papers

Title	Date	Tasks	Status
Open-Set Domain Adaptation with Visual-Language Foundation Models	Jul 30, 2023	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Multi-Source Domain Adaptation through Dataset Dictionary Learning in Wasserstein Space	Jul 27, 2023	Dictionary LearningDomain Adaptation	CodeCode Available
Dynamic Domain Discrepancy Adjustment for Active Multi-Domain Adaptation	Jul 26, 2023	Domain AdaptationMulti-Source Unsupervised Domain Adaptation	—Unverified
ChildGAN: Large Scale Synthetic Child Facial Data Using Domain Adaptation in StyleGAN	Jul 25, 2023	Domain AdaptationTransfer Learning	—Unverified
SL: Stable Learning in Source-Free Domain Adaption for Medical Image Segmentation	Jul 24, 2023	Domain AdaptationImage Segmentation	—Unverified
EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge: Mixed Sequences Prediction	Jul 24, 2023	Action RecognitionDomain Adaptation	—Unverified
MatSpectNet: Material Segmentation Network with Domain-Aware and Physically-Constrained Hyperspectral Reconstruction	Jul 21, 2023	Domain AdaptationMaterial Segmentation	CodeCode Available
Feed-Forward Source-Free Domain Adaptation via Class Prototypes	Jul 20, 2023	Domain AdaptationSource-Free Domain Adaptation	—Unverified
Properties of Discrete Sliced Wasserstein Losses	Jul 19, 2023	Domain Adaptation	—Unverified
Unsupervised Accuracy Estimation of Deep Visual Models using Domain-Adaptive Adversarial Perturbation without Source Samples	Jul 19, 2023	Domain AdaptationSource-Free Domain Adaptation	—Unverified
Causality-oriented robustness: exploiting general noise interventions	Jul 18, 2023	Causal InferenceDomain Adaptation	CodeCode Available
Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives	Jul 18, 2023	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public Cloud	Jul 18, 2023	CPUDecision Making	CodeCode Available
Domain Adaptation using Silver Standard Masks for Lateral Ventricle Segmentation in FLAIR MRI	Jul 17, 2023	Domain AdaptationTransfer Learning	—Unverified
Similarity Min-Max: Zero-Shot Day-Night Domain Adaptation	Jul 17, 2023	Action RecognitionDomain Adaptation	—Unverified
PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation	Jul 14, 2023	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Unsupervised Domain Adaptation using Lexical Transformations and Label Injection for Twitter Data	Jul 14, 2023	Domain AdaptationPart-Of-Speech Tagging	—Unverified
Population Expansion for Training Language Models with Private Federated Learning	Jul 14, 2023	Domain AdaptationFederated Learning	—Unverified
Watch Where You Head: A View-biased Domain Gap in Gait Recognition and Unsupervised Adaptation	Jul 13, 2023	Domain AdaptationGait Recognition	—Unverified
A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023	Jul 13, 2023	Action RecognitionDomain Adaptation	—Unverified
Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations	Jul 12, 2023	Domain Adaptation	—Unverified
Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-Answering	Jul 12, 2023	Domain AdaptationGenerative Question Answering	—Unverified
Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images	Jul 11, 2023	DeblurringDomain Adaptation	—Unverified
One-Shot Learning for Periocular Recognition: Exploring the Effect of Domain Adaptation and Data Bias on Deep Representations	Jul 11, 2023	Domain AdaptationOne-Shot Learning	—Unverified
Advances and Challenges in Meta-Learning: A Technical Review	Jul 10, 2023	Continual LearningDomain 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