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 40014050 of 6439 papers

TitleStatusHype
Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation0
Unsupervised Domain Adaptation of Black-Box Source ModelsCode0
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac SegmentationCode1
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation0
Adaptiope: A Modern Benchmark for Unsupervised Domain AdaptationCode0
Domain-aware Neural Language Models for Speech Recognition0
Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation0
Learn by Guessing: Multi-Step Pseudo-Label Refinement for Person Re-Identification0
Style Normalization and Restitution for Domain Generalization and AdaptationCode1
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation0
The Highs and Lows of Simple Lexical Domain Adaptation Approaches for Neural Machine Translation0
Domain Adaptation for the Segmentation of Confidential Medical ImagesCode0
Active Universal Domain Adaptation0
Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation0
Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective0
Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection0
CDS: Cross-Domain Self-Supervised Pre-Training0
Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality AssessmentCode1
Self-Supervised Vessel Segmentation via Adversarial LearningCode1
Self-Supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images0
STEM: An Approach to Multi-Source Domain Adaptation With GuaranteesCode0
Collaborative Learning With Disentangled Features for Zero-Shot Domain Adaptation0
Knowledge Mining and Transferring for Domain Adaptive Object DetectionCode0
BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic SegmentationCode1
Weak Adaptation Learning: Addressing Cross-Domain Data Insufficiency With Weak Annotator0
Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation0
Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point CloudsCode1
Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images0
Gradient Distribution Alignment Certificates Better Adversarial Domain AdaptationCode1
Learning Causal Representation for Training Cross-Domain Pose Estimator via Generative Interventions0
Adaptive Adversarial Network for Source-Free Domain Adaptation0
S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain AdaptationCode1
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis0
Energy-constrained Self-training for Unsupervised Domain Adaptation0
B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-LearningCode0
Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks0
Mirror Sample Based Distribution Alignment for Unsupervised Domain Adaption0
Sample Balancing for Improving Generalization under Distribution Shifts0
Cross-Modal Domain Adaptation for Reinforcement LearningCode1
Neighbor Class Consistency on Unsupervised Domain Adaptation0
Collaborative Normalization for Unsupervised Domain Adaptation0
A Simple Unified Information Regularization Framework for Multi-Source Domain Adaptation0
Unsupervised Domain Adaptation via Minimized Joint Error0
Multi-EPL: Accurate Multi-source Domain Adaptation0
Disentangling style and content for low resource video domain adaptation: a case study on keystroke inference attacks0
Disentangled cyclic reconstruction for domain adaptation0
Learning Robust Models by Countering Spurious Correlations0
Counterfactual Self-Training0
Learning to Generate the Unknowns for Open-set Domain Adaptation0
EMTL: A Generative Domain Adaptation Approach0
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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