SOTAVerified

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.

Further readings:

( Image credit: Unsupervised Image-to-Image Translation Networks )

Papers

Showing 49515000 of 6439 papers

TitleStatusHype
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCICode0
Towards Resolving Propensity Contradiction in Offline Recommender LearningCode0
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup SegmentationCode0
FewRel 2.0: Towards More Challenging Few-Shot Relation ClassificationCode0
Learning Generalisable Omni-Scale Representations for Person Re-IdentificationCode1
Wasserstein Distance Guided Cross-Domain Learning0
Deep Semantic Parsing of Freehand Sketches with Homogeneous Transformation, Soft-Weighted Loss, and Staged Learning0
Manifold Embedded Knowledge Transfer for Brain-Computer InterfacesCode0
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems0
The Role of Embedding Complexity in Domain-invariant RepresentationsCode0
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain AdaptationCode0
Bayesian Meta-Learning for the Few-Shot Setting via Deep KernelsCode1
ErrorNet: Learning error representations from limited data to improve vascular segmentation0
MixMatch Domain Adaptaion: Prize-winning solution for both tracks of VisDA 2019 challengeCode0
Learning to Generalize One Sample at a Time with Self-Supervision0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding0
Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019Code0
ATL: Autonomous Knowledge Transfer from Many Streaming ProcessesCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation0
Domain Differential Adaptation for Neural Machine TranslationCode0
A General Upper Bound for Unsupervised Domain Adaptation0
Tree-Structured Semantic Encoder with Knowledge Sharing for Domain Adaptation in Natural Language Generation0
Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation0
Unsupervised Graph Association for Person Re-IdentificationCode0
Deep Head Pose Estimation Using Synthetic Images and Partial Adversarial Domain Adaption for Continuous Label Spaces0
SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation0
Racial Faces in the Wild: Reducing Racial Bias by Information Maximization Adaptation Network0
Batch Weight for Domain Adaptation With Mass Shift0
Attention Bridging Network for Knowledge Transfer0
Domain Adaptation for Semantic Segmentation with Maximum Squares LossCode0
MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent LabelingCode0
Wasserstein-2 Generative NetworksCode1
Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation0
Unsupervised Domain Adaptation through Self-SupervisionCode0
Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification0
Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection0
Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment0
Wildly Unsupervised Domain Adaptation and Its Powerful and Efficient Solution0
Unsupervised domain adaptation with imputation0
Domain-invariant Learning using Adaptive Filter Decomposition0
An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms0
Domain-Invariant Representations: A Look on Compression and Weights0
Multi-Step Decentralized Domain Adaptation0
Domain Adaptation via Low-Rank Basis Approximation0
Adapting to Label Shift with Bias-Corrected Calibration0
Transfer Alignment Network for Double Blind Unsupervised Domain Adaptation0
Distribution Matching Prototypical Network for Unsupervised Domain Adaptation0
PROTOTYPE-ASSISTED ADVERSARIAL LEARNING FOR UNSUPERVISED DOMAIN ADAPTATION0
Hope For The Best But Prepare For The Worst: Cautious Adaptation In RL Agents0
Adversarial Inductive Transfer Learning with input and output space adaptation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FFTATAverage Accuracy96Unverified
2PMTransAverage Accuracy95.3Unverified
3CMKDAverage Accuracy94.4Unverified
4SSRT-B (ours)Average Accuracy93.5Unverified
5CDTransAverage Accuracy92.6Unverified
6CoViAverage Accuracy91.8Unverified
7GSDEAverage Accuracy91.7Unverified
8FixBiAverage Accuracy91.4Unverified
9Contrastive Adaptation NetworkAverage Accuracy90.6Unverified
10BIWAAAverage Accuracy90.5Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU78.1Unverified
2ILM-ASSLmIoU76.6Unverified
3DCFmIoU69.3Unverified
4HRDA+PiPamIoU68.2Unverified
5MICmIoU67.3Unverified
6FREDOM - TransformermIoU67Unverified
7HRDAmIoU65.8Unverified
8SePiComIoU64.3Unverified
9MIC + Guidance TrainingmIoU63.8Unverified
10DAFormer + ProCSTmIoU61.6Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU77.8Unverified
2DCFmIoU77.7Unverified
3ILM-ASSLmIoU76.1Unverified
4MICmIoU75.9Unverified
5HRDA+PiPamIoU75.6Unverified
6HRDAmIoU73.8Unverified
7FREDOM - TransformermIoU73.6Unverified
8HALOmIoU73.3Unverified
9SePiComIoU70.3Unverified
10DAFormer + ProCSTmIoU69.4Unverified
#ModelMetricClaimedVerifiedStatus
1SWGAccuracy92.3Unverified
2RCLAccuracy90Unverified
3PGA (ViT-L/14)Accuracy89.4Unverified
4PMTransAccuracy89Unverified
5CMKDAccuracy89Unverified
6MICAccuracy86.2Unverified
7PGA (ViT-B/16)Accuracy85.1Unverified
8ELSAccuracy84.6Unverified
9SDAT (ViT-B/16)Accuracy84.3Unverified
10CDTrans (DeiT-B)Accuracy80.5Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy93.8Unverified
2RCLAccuracy93.2Unverified
3MICAccuracy92.8Unverified
4SWGAccuracy92.7Unverified
5CMKDAccuracy91.8Unverified
6DePTAccuracy90.7Unverified
7SDAT(ViT)Accuracy89.8Unverified
8SFDA2++Accuracy89.6Unverified
9PMtransAccuracy88.8Unverified
10CoViAccuracy88.5Unverified
#ModelMetricClaimedVerifiedStatus
1CMKDAccuracy94.3Unverified
2MCC+NWDAccuracy90.7Unverified
3GLOT-DRAccuracy90.4Unverified
4SPLAccuracy90.3Unverified
5DFA-SAFNAccuracy90.2Unverified
6DADAAccuracy89.3Unverified
7DFA-ENTAccuracy89.1Unverified
8MEDMAccuracy88.9Unverified
9DDAAccuracy88.9Unverified
10IAFN+ENTAccuracy88.9Unverified
#ModelMetricClaimedVerifiedStatus
1SoRAmIoU78.8Unverified
2ReinmIoU77.6Unverified
3CoDAmIoU72.6Unverified
4Refign (HRDA)mIoU72.1Unverified
5HALOmIoU71.9Unverified
6MICmIoU70.4Unverified
7HRDAmIoU68Unverified
8Refign (DAFormer)mIoU65.5Unverified
9VBLC (DAFormer)mIoU64.2Unverified
10CMFormermIoU60.1Unverified
#ModelMetricClaimedVerifiedStatus
1FACTAccuracy98.8Unverified
2FAMCDAccuracy98.72Unverified
3DFA-MCDAccuracy98.6Unverified
4Mean teacherAccuracy98.26Unverified
5DRANetAccuracy98.2Unverified
6SHOTAccuracy98Unverified
7DFA-ENTAccuracy97.9Unverified
8CyCleGAN (Light-weight Calibrator)Accuracy97.1Unverified