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 1676–1700 of 6439 papers

Title	Date	Tasks	Status	Hype
Watch Where You Head: A View-biased Domain Gap in Gait Recognition and Unsupervised Adaptation	Jul 13, 2023	Domain AdaptationGait Recognition	—Unverified	0
Copy Is All You Need	Jul 13, 2023	AllDomain Adaptation	CodeCode Available	1
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	0
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	0
Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations	Jul 12, 2023	Domain Adaptation	—Unverified	0
Uni-Removal: A Semi-Supervised Framework for Simultaneously Addressing Multiple Degradations in Real-World Images	Jul 11, 2023	DeblurringDomain Adaptation	—Unverified	0
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	0
Unsupervised Domain Adaptation with Deep Neural-Network	Jul 10, 2023	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	0
Advances and Challenges in Meta-Learning: A Technical Review	Jul 10, 2023	Continual LearningDomain Adaptation	—Unverified	0
Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology	Jul 10, 2023	Data AugmentationDomain Adaptation	CodeCode Available	1
Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation	Jul 9, 2023	3D Semantic SegmentationDomain Adaptation	—Unverified	0
Domain Adaptation using Silver Standard Labels for Ki-67 Scoring in Digital Pathology: A Step Closer to Widescale Deployment	Jul 8, 2023	Domain Adaptation	—Unverified	0
Interactive Learning of Intrinsic and Extrinsic Properties for All-day Semantic Segmentation	Jul 7, 2023	AllAll-day Semantic Segmentation	CodeCode Available	1
Universal Semi-supervised Model Adaptation via Collaborative Consistency Training	Jul 7, 2023	Domain Adaptation	—Unverified	0
Efficient Domain Adaptation of Sentence Embeddings Using Adapters	Jul 6, 2023	Domain AdaptationSemantic Similarity	—Unverified	0
Label-Synchronous Neural Transducer for End-to-End ASR	Jul 6, 2023	Domain AdaptationPrediction	—Unverified	0
Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation	Jul 6, 2023	Binary ClassificationDiagnostic	—Unverified	0
Dense Retrieval Adaptation using Target Domain Description	Jul 6, 2023	Domain AdaptationInformation Retrieval	—Unverified	0
Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning	Jul 6, 2023	Contrastive LearningDecoder	CodeCode Available	1
Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain	Jul 6, 2023	Domain Adaptationparameter-efficient fine-tuning	CodeCode Available	1
Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification	Jul 6, 2023	BenchmarkingDomain Adaptation	CodeCode Available	1
Prompting Diffusion Representations for Cross-Domain Semantic Segmentation	Jul 5, 2023	Domain AdaptationDomain Generalization	CodeCode Available	0
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation	Jul 4, 2023	Domain AdaptationImage Generation	—Unverified	0
FREEDOM: Target Label & Source Data & Domain Information-Free Multi-Source Domain Adaptation for Unsupervised Personalization	Jul 4, 2023	Domain AdaptationPhilosophy	—Unverified	0
Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios	Jul 4, 2023	DiagnosticDomain Adaptation	—Unverified	0

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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