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 5976–6000 of 6439 papers

Title	Date	Tasks	Status	Hype
Unsupervised Cross-Domain Image Generation	Nov 7, 2016	Domain AdaptationImage Generation	CodeCode Available	2
Domain Adaptation For Formant Estimation Using Deep Learning	Nov 6, 2016	Deep LearningDomain Adaptation	—Unverified	0
Learning to Pivot with Adversarial Networks	Nov 3, 2016	Domain AdaptationFairness	CodeCode Available	0
Learning Sentence Embeddings with Auxiliary Tasks for Cross-Domain Sentiment Classification	Nov 1, 2016	Domain AdaptationGeneral Classification	—Unverified	0
Bilingually-constrained Synthetic Data for Implicit Discourse Relation Recognition	Nov 1, 2016	Domain AdaptationMachine Translation	—Unverified	0
PaCCSS-IT: A Parallel Corpus of Complex-Simple Sentences for Automatic Text Simplification	Nov 1, 2016	Dependency ParsingDomain Adaptation	—Unverified	0
Supervised Distributional Hypernym Discovery via Domain Adaptation	Nov 1, 2016	ClusteringDomain Adaptation	—Unverified	0
Neural Network for Heterogeneous Annotations	Nov 1, 2016	Dependency ParsingDomain Adaptation	—Unverified	0
Modeling Skip-Grams for Event Detection with Convolutional Neural Networks	Nov 1, 2016	Domain AdaptationEvent Detection	—Unverified	0
Automatic Features for Essay Scoring -- An Empirical Study	Nov 1, 2016	Automated Essay ScoringDomain Adaptation	—Unverified	0
A General Regularization Framework for Domain Adaptation	Nov 1, 2016	Domain AdaptationMulti-Task Learning	—Unverified	0
Towards a continuous modeling of natural language domains	Oct 28, 2016	Domain AdaptationLanguage Modeling	—Unverified	0
Professor Forcing: A New Algorithm for Training Recurrent Networks	Oct 27, 2016	Domain AdaptationHandwriting generation	CodeCode Available	0
From Traditional to Modern : Domain Adaptation for Action Classification in Short Social Video Clips	Oct 18, 2016	Action ClassificationData Augmentation	—Unverified	0
Personalized Machine Translation: Preserving Original Author Traits	Oct 18, 2016	Domain AdaptationMachine Translation	—Unverified	0
Deep Learning Prototype Domains for Person Re-Identification	Oct 17, 2016	Deep LearningDomain Adaptation	—Unverified	0
Theoretical Analysis of Domain Adaptation with Optimal Transport	Oct 14, 2016	Domain Adaptation	—Unverified	0
ILGNet: Inception Modules with Connected Local and Global Features for Efficient Image Aesthetic Quality Classification using Domain Adaptation	Oct 7, 2016	Aesthetics Quality AssessmentDomain Adaptation	CodeCode Available	0
Domain Adaptation with Soft-margin multiple feature-kernel learning beats Deep Learning for surveillance face recognition	Oct 5, 2016	Domain AdaptationFace Recognition	—Unverified	0
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles	Oct 5, 2016	Domain AdaptationReinforcement Learning	—Unverified	0
Neural Structural Correspondence Learning for Domain Adaptation	Oct 5, 2016	DenoisingDomain Adaptation	CodeCode Available	0
Kernel Selection using Multiple Kernel Learning and Domain Adaptation in Reproducing Kernel Hilbert Space, for Face Recognition under Surveillance Scenario	Oct 3, 2016	Domain AdaptationFace Recognition	—Unverified	0
Multi-domain Adaptation for Statistical Machine Translation Based on Feature Augmentation	Oct 1, 2016	Domain AdaptationMachine Translation	—Unverified	0
Adding syntactic structure to bilingual terminology for improved domain adaptation	Oct 1, 2016	Domain AdaptationMachine Translation	—Unverified	0
Dialogue manager domain adaptation using Gaussian process reinforcement learning	Sep 9, 2016	Domain AdaptationGaussian Processes	—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