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 4576–4600 of 6439 papers

Title	Date	Tasks	Status	Hype
Neural Unsupervised Domain Adaptation in NLP---A Survey	May 31, 2020	Domain AdaptationOut-of-Distribution Generalization	CodeCode Available	1
Self-adaptive Re-weighted Adversarial Domain Adaptation	May 30, 2020	Domain AdaptationTriplet	—Unverified	0
Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move's discrepancies	May 28, 2020	Domain AdaptationImage Registration	—Unverified	0
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation	May 28, 2020	Domain AdaptationImage Segmentation	CodeCode Available	1
Language Models are Few-Shot Learners	May 28, 2020	answerability predictionArticles	CodeCode Available	3
Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation	May 28, 2020	DisentanglementDomain Adaptation	—Unverified	0
Balanced joint maximum mean discrepancy for deep transfer learning	May 27, 2020	Domain AdaptationImage Classification	CodeCode Available	0
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure	May 27, 2020	BIG-bench Machine LearningDomain Adaptation	CodeCode Available	1
Kernel methods library for pattern analysis and machine learning in python	May 27, 2020	BIG-bench Machine LearningDomain Adaptation	CodeCode Available	1
Co-Heterogeneous and Adaptive Segmentation from Multi-Source and Multi-Phase CT Imaging Data: A Study on Pathological Liver and Lesion Segmentation	May 27, 2020	Computed Tomography (CT)Domain Adaptation	—Unverified	0
Unsupervised Domain Expansion from Multiple Sources	May 26, 2020	Domain AdaptationUnsupervised Domain Expansion	—Unverified	0
Keep it Simple: Image Statistics Matching for Domain Adaptation	May 26, 2020	Domain Adaptation	CodeCode Available	1
Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation	May 25, 2020	Domain AdaptationUnsupervised Domain Adaptation	—Unverified	0
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping	May 25, 2020	Domain AdaptationManagement	CodeCode Available	0
A Joint Pixel and Feature Alignment Framework for Cross-dataset Palmprint Recognition	May 25, 2020	Data AugmentationDomain Adaptation	CodeCode Available	1
Knowledge Graph Simple Question Answering for Unseen Domains	May 25, 2020	Domain AdaptationQuestion Answering	CodeCode Available	1
Incremental Real-Time Personalization in Human Activity Recognition Using Domain Adaptive Batch Normalization	May 25, 2020	Activity RecognitionDomain Adaptation	—Unverified	0
Discriminative Active Learning for Domain Adaptation	May 24, 2020	Active LearningDiversity	—Unverified	0
Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation	May 22, 2020	Domain Adaptation	CodeCode Available	0
SODA: Detecting Covid-19 in Chest X-rays with Semi-supervised Open Set Domain Adaptation	May 22, 2020	Domain Adaptationimage-classification	—Unverified	0
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data	May 22, 2020	Domain AdaptationTime Series	CodeCode Available	1
Style Normalization and Restitution for Generalizable Person Re-identification	May 22, 2020	DisentanglementDomain Adaptation	CodeCode Available	1
Unsupervised Domain Adaptation in Semantic Segmentation: a Review	May 21, 2020	Autonomous DrivingDomain Adaptation	—Unverified	0
Cross-Domain Few-Shot Learning with Meta Fine-Tuning	May 21, 2020	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified	0
ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance	May 21, 2020	AttributeClustering	CodeCode Available	1

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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