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 5251–5275 of 6439 papers

Title	Date	Tasks	Status
WUT at SemEval-2019 Task 9: Domain-Adversarial Neural Networks for Domain Adaptation in Suggestion Mining	Jun 1, 2019	Domain AdaptationGeneral Classification	—Unverified
Gradient Matching Generative Networks for Zero-Shot Learning	Jun 1, 2019	Domain AdaptationGeneral Classification	CodeCode Available
Simplified Neural Unsupervised Domain Adaptation	Jun 1, 2019	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Consensus Clustering: An Embedding Perspective, Extension and Beyond	May 31, 2019	ClusteringConstrained Clustering	—Unverified
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows	May 30, 2019	Density EstimationDomain Adaptation	CodeCode Available
Discriminative Clustering for Robust Unsupervised Domain Adaptation	May 30, 2019	ClusteringDomain Adaptation	—Unverified
Batch weight for domain adaptation with mass shift	May 29, 2019	Domain AdaptationImage-to-Image Translation	—Unverified
d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding	May 29, 2019	Domain Adaptation	CodeCode Available
Adversarial Domain Adaptation Being Aware of Class Relationships	May 28, 2019	Domain AdaptationTransfer Learning	—Unverified
Domain Generalization via Universal Non-volume Preserving Models	May 28, 2019	Domain AdaptationDomain Generalization	—Unverified
Image Alignment in Unseen Domains via Domain Deep Generalization	May 28, 2019	Deep LearningDomain Adaptation	—Unverified
Domain-Specific Batch Normalization for Unsupervised Domain Adaptation	May 27, 2019	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available
ET-GAN: Cross-Language Emotion Transfer Based on Cycle-Consistent Generative Adversarial Networks	May 27, 2019	Domain AdaptationGenerative Adversarial Network	—Unverified
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation	May 26, 2019	Domain AdaptationPartial Domain Adaptation	—Unverified
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport	May 26, 2019	Domain Adaptation	—Unverified
DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns	May 26, 2019	Domain AdaptationRecommendation Systems	CodeCode Available
Unsupervised Domain Adaptation via Regularized Conditional Alignment	May 26, 2019	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
Learning Smooth Representation for Unsupervised Domain Adaptation	May 26, 2019	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available
Domain Adaptive Attention Learning for Unsupervised Person Re-Identification	May 25, 2019	DiversityDomain Adaptation	—Unverified
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections	May 24, 2019	Domain AdaptationWord Embeddings	CodeCode Available
Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation	May 24, 2019	Domain Adaptation	—Unverified
Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data	May 22, 2019	Domain AdaptationUnsupervised Domain Adaptation	—Unverified
A Joint Named-Entity Recognizer for Heterogeneous Tag-sets Using a Tag Hierarchy	May 22, 2019	Domain Adaptationnamed-entity-recognition	—Unverified
Joint Information Preservation for Heterogeneous Domain Adaptation	May 22, 2019	Domain Adaptation	—Unverified
Simplified Neural Unsupervised Domain Adaptation	May 22, 2019	Domain AdaptationUnsupervised Domain Adaptation	—Unverified

Show:10 25 50

← PrevPage 211 of 258Next →

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