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 5726–5750 of 6439 papers

Title	Date	Tasks	Status	Hype
Multiple Source Domain Adaptation with Adversarial Learning	Jan 1, 2018	Domain AdaptationSentiment Analysis	—Unverified	0
Large Scale Optimal Transport and Mapping Estimation	Jan 1, 2018	Domain Adaptation	—Unverified	0
Discriminative and Geometry Aware Unsupervised Domain Adaptation	Dec 28, 2017	Domain Adaptationimage-classification	—Unverified	0
Domain Adaptation Meets Disentangled Representation Learning and Style Transfer	Dec 25, 2017	Domain AdaptationRepresentation Learning	—Unverified	0
Incremental Adversarial Domain Adaptation for Continually Changing Environments	Dec 20, 2017	Domain AdaptationGenerative Adversarial Network	—Unverified	0
SuperPoint: Self-Supervised Interest Point Detection and Description	Dec 20, 2017	Domain AdaptationHomography Estimation	CodeCode Available	1
Structured Optimal Transport	Dec 17, 2017	BIG-bench Machine LearningDomain Adaptation	—Unverified	0
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency	Dec 15, 2017	Domain AdaptationKeypoint Estimation	CodeCode Available	0
Can We Teach Computers to Understand Art? Domain Adaptation for Enhancing Deep Networks Capacity to De-Abstract Art	Dec 11, 2017	Domain AdaptationStyle Transfer	—Unverified	0
Domain Adaptation Using Adversarial Learning for Autonomous Navigation	Dec 11, 2017	Autonomous NavigationDomain Adaptation	—Unverified	0
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation	Dec 7, 2017	Domain Adaptationimage-classification	CodeCode Available	1
Stretching Domain Adaptation: How far is too far?	Dec 6, 2017	Domain AdaptationUnsupervised Domain Adaptation	—Unverified	0
Unsupervised Multi-Domain Image Translation with Domain-Specific Encoders/Decoders	Dec 6, 2017	DecoderDomain Adaptation	—Unverified	0
The Samsung and University of Edinburgh’s submission to IWSLT17	Dec 1, 2017	Decoderde-en	—Unverified	0
The RWTH Aachen Machine Translation Systems for IWSLT 2017	Dec 1, 2017	Domain AdaptationMachine Translation	—Unverified	0
Population Matching Discrepancy and Applications in Deep Learning	Dec 1, 2017	Deep LearningDomain Adaptation	—Unverified	0
Matching on Balanced Nonlinear Representations for Treatment Effects Estimation	Dec 1, 2017	counterfactualDomain Adaptation	—Unverified	0
Neural Regularized Domain Adaptation for Chinese Word Segmentation	Dec 1, 2017	Chinese Word SegmentationDomain Adaptation	—Unverified	0
Image to Image Translation for Domain Adaptation	Dec 1, 2017	Domain AdaptationImage-to-Image Translation	—Unverified	0
ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes	Nov 30, 2017	Domain AdaptationSegmentation	—Unverified	0
Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation	Nov 28, 2017	Domain AdaptationGeneral Classification	CodeCode Available	0
Learning to cluster in order to transfer across domains and tasks	Nov 28, 2017	ClusteringConstrained Clustering	CodeCode Available	0
Adversarial Transfer Learning for Cross-domain Visual Recognition	Nov 24, 2017	Domain AdaptationTransfer Learning	—Unverified	0
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery	Nov 24, 2017	Domain AdaptationMulti-Task Learning	CodeCode Available	0
Unsupervised Domain Adaptation with Similarity Learning	Nov 24, 2017	Domain AdaptationGeneral Classification	—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