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 2476–2500 of 6439 papers

Title	Date	Tasks	Status
Cross-modal and Cross-domain Knowledge Transfer for Label-free 3D Segmentation	Sep 19, 2023	Domain AdaptationSemantic Segmentation	—Unverified
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation	Sep 19, 2023	Domain AdaptationMulti-target Domain Adaptation	—Unverified
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models	Sep 18, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Improved Factorized Neural Transducer Model For text-only Domain Adaptation	Sep 18, 2023	DecoderDomain Adaptation	—Unverified
Making the Full Model Adaptive: Multi-level Domain Adaptation for Multi-Domain CTR Prediction	Sep 17, 2023	Click-Through Rate PredictionDomain Adaptation	—Unverified
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification	Sep 17, 2023	Data AugmentationDiversity	—Unverified
Tightening Classification Boundaries in Open Set Domain Adaptation through Unknown Exploitation	Sep 16, 2023	Data AugmentationDomain Adaptation	—Unverified
t-SOT FNT: Streaming Multi-talker ASR with Text-only Domain Adaptation Capability	Sep 15, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
DA-RAW: Domain Adaptive Object Detection for Real-World Adverse Weather Conditions	Sep 15, 2023	Contrastive LearningDomain Adaptation	—Unverified
T-UDA: Temporal Unsupervised Domain Adaptation in Sequential Point Clouds	Sep 15, 2023	3D Semantic SegmentationDomain Adaptation	CodeCode Available
Neural Machine Translation Models Can Learn to be Few-shot Learners	Sep 15, 2023	Domain AdaptationIn-Context Learning	—Unverified
Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy	Sep 14, 2023	Contrastive LearningDomain Adaptation	CodeCode Available
Federated Dataset Dictionary Learning for Multi-Source Domain Adaptation	Sep 14, 2023	Dictionary LearningDomain Adaptation	—Unverified
Multi-Source Domain Adaptation meets Dataset Distillation through Dataset Dictionary Learning	Sep 14, 2023	Dataset DistillationDictionary Learning	—Unverified
A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation	Sep 12, 2023	Domain AdaptationImage Segmentation	—Unverified
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection	Sep 12, 2023	Active LearningDomain Adaptation	CodeCode Available
AstroLLaMA: Towards Specialized Foundation Models in Astronomy	Sep 12, 2023	AstronomyCausal Language Modeling	—Unverified
Strong-Weak Integrated Semi-supervision for Unsupervised Single and Multi Target Domain Adaptation	Sep 12, 2023	DiversityDomain Adaptation	—Unverified
Cross-tokamak Disruption Prediction based on Physics-Guided Feature Extraction and domain adaptation	Sep 11, 2023	DiagnosticDomain Adaptation	—Unverified
DAD++: Improved Data-free Test Time Adversarial Defense	Sep 10, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available
Weighted Unsupervised Domain Adaptation Considering Geometry Features and Engineering Performance of 3D Design Data	Sep 8, 2023	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Better Practices for Domain Adaptation	Sep 7, 2023	BenchmarkingDomain Adaptation	—Unverified
A Robust Negative Learning Approach to Partial Domain Adaptation Using Source Prototypes	Sep 7, 2023	Domain AdaptationEnsemble Learning	—Unverified
Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation	Sep 6, 2023	DecoderDomain Adaptation	—Unverified
Domain Adaptation for Satellite-Borne Hyperspectral Cloud Detection	Sep 5, 2023	Cloud DetectionDomain 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