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 4001–4025 of 6439 papers

Title	Date	Tasks	Status	Hype
Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation	Jan 9, 2021	Domain Adaptationregression	—Unverified	0
Unsupervised Domain Adaptation of Black-Box Source Models	Jan 8, 2021	Domain AdaptationLearning with noisy labels	CodeCode Available	0
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation	Jan 7, 2021	Cardiac SegmentationDomain Adaptation	CodeCode Available	1
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation	Jan 6, 2021	Domain AdaptationPartial Domain Adaptation	—Unverified	0
Adaptiope: A Modern Benchmark for Unsupervised Domain Adaptation	Jan 5, 2021	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	0
Domain-aware Neural Language Models for Speech Recognition	Jan 5, 2021	Domain Adaptationdomain classification	—Unverified	0
Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation	Jan 5, 2021	Domain AdaptationSemi-supervised Domain Adaptation	—Unverified	0
Learn by Guessing: Multi-Step Pseudo-Label Refinement for Person Re-Identification	Jan 4, 2021	ClusteringDomain Adaptation	—Unverified	0
Style Normalization and Restitution for Domain Generalization and Adaptation	Jan 3, 2021	DisentanglementDomain Adaptation	CodeCode Available	1
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation	Jan 3, 2021	Domain AdaptationMusic Source Separation	—Unverified	0
The Highs and Lows of Simple Lexical Domain Adaptation Approaches for Neural Machine Translation	Jan 2, 2021	DecoderDomain Adaptation	—Unverified	0
Domain Adaptation for the Segmentation of Confidential Medical Images	Jan 2, 2021	Domain AdaptationImage Segmentation	CodeCode Available	0
Active Universal Domain Adaptation	Jan 1, 2021	Active LearningDomain Adaptation	—Unverified	0
Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation	Jan 1, 2021	Domain AdaptationDomain Generalization	—Unverified	0
Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective	Jan 1, 2021	Domain AdaptationImage-to-Image Translation	—Unverified	0
Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection	Jan 1, 2021	Domain AdaptationGraph Learning	—Unverified	0
CDS: Cross-Domain Self-Supervised Pre-Training	Jan 1, 2021	Domain AdaptationTransfer Learning	—Unverified	0
Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality Assessment	Jan 1, 2021	Domain AdaptationUnsupervised Domain Adaptation	CodeCode Available	1
Self-Supervised Vessel Segmentation via Adversarial Learning	Jan 1, 2021	Domain AdaptationSegmentation	CodeCode Available	1
Self-Supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images	Jan 1, 2021	Domain AdaptationSelf-Supervised Learning	—Unverified	0
STEM: An Approach to Multi-Source Domain Adaptation With Guarantees	Jan 1, 2021	Domain AdaptationMulti-Source Unsupervised Domain Adaptation	CodeCode Available	0
Collaborative Learning With Disentangled Features for Zero-Shot Domain Adaptation	Jan 1, 2021	Domain Adaptation	—Unverified	0
Knowledge Mining and Transferring for Domain Adaptive Object Detection	Jan 1, 2021	AttributeDomain Adaptation	CodeCode Available	0
BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic Segmentation	Jan 1, 2021	Domain AdaptationSegmentation	CodeCode Available	1
Weak Adaptation Learning: Addressing Cross-Domain Data Insufficiency With Weak Annotator	Jan 1, 2021	Domain 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