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 5701–5725 of 6439 papers

Title	Date	Tasks	Status
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task	Apr 16, 2018	Domain AdaptationGrammatical Error Correction	CodeCode Available
Cross-Domain Visual Recognition via Domain Adaptive Dictionary Learning	Apr 12, 2018	Dictionary LearningDomain Adaptation	—Unverified
Causal Generative Domain Adaptation Networks	Apr 12, 2018	Computational EfficiencyDomain Adaptation	—Unverified
Adversarial Alignment of Class Prediction Uncertainties for Domain Adaptation	Apr 12, 2018	Domain Adaptationimage-classification	—Unverified
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model	Apr 10, 2018	Domain AdaptationFace Generation	CodeCode Available
Improving Confidence Estimates for Unfamiliar Examples	Apr 9, 2018	AttributeDomain Adaptation	CodeCode Available
Domain Adaptation for Statistical Machine Translation	Apr 5, 2018	Domain AdaptationMachine Translation	—Unverified
Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation	Apr 2, 2018	Domain AdaptationTransfer Learning	—Unverified
Generative Adversarial Learning for Spectrum Sensing	Apr 2, 2018	BIG-bench Machine LearningData Augmentation	—Unverified
Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling	Mar 31, 2018	Dialogue ManagementDomain Adaptation	CodeCode Available
A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation	Mar 27, 2018	Domain AdaptationGenerative Adversarial Network	—Unverified
DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation	Mar 27, 2018	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available
Importance Weighted Adversarial Nets for Partial Domain Adaptation	Mar 25, 2018	Domain AdaptationPartial Domain Adaptation	—Unverified
Unsupervised Domain Adaptation: A Multi-task Learning-based Method	Mar 25, 2018	Domain AdaptationMulti-Task Learning	—Unverified
Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld	Mar 24, 2018	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer Networks	Mar 22, 2018	Camera CalibrationDomain Adaptation	CodeCode Available
Domain Adaptation for Ear Recognition Using Deep Convolutional Neural Networks	Mar 21, 2018	Domain Adaptation	CodeCode Available
Domain Adaptation with Randomized Expectation Maximization	Mar 20, 2018	Domain AdaptationTransfer Learning	CodeCode Available
Monocular Fisheye Camera Depth Estimation Using Sparse LiDAR Supervision	Mar 16, 2018	Depth EstimationDomain Adaptation	—Unverified
Domain Adaptation on Graphs by Learning Aligned Graph Bases	Mar 14, 2018	Domain AdaptationGeneral Classification	—Unverified
Optimal Transport for Multi-source Domain Adaptation under Target Shift	Mar 13, 2018	Domain AdaptationImage Segmentation	CodeCode Available
Cross-domain Recommendation via Deep Domain Adaptation	Mar 8, 2018	Collaborative FilteringDenoising	—Unverified
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation	Mar 5, 2018	Depth EstimationDomain Adaptation	—Unverified
Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift	Mar 2, 2018	Domain AdaptationMulti-Source Unsupervised Domain Adaptation	CodeCode Available
Joint Training for Neural Machine Translation Models with Monolingual Data	Mar 1, 2018	Domain AdaptationMachine Translation	—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