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 28512900 of 6439 papers

TitleStatusHype
Contrastive Regression for Domain Adaptation on Gaze Estimation0
CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation0
Event Recognition in Videos by Learning from Heterogeneous Web Sources0
Baidu Neural Machine Translation Systems for WMT190
A Comprehensive Framework for Semantic Similarity Analysis of Human and AI-Generated Text Using Transformer Architectures and Ensemble Techniques0
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies0
Adversarial Multiple Source Domain Adaptation0
Improving both domain robustness and domain adaptability in machine translation0
Evaluation of Transfer Learning and Domain Adaptation for Analyzing German-Speaking Job Advertisements0
Evaluation of the domain adaptation of MT systems in ACCURAT0
Evaluation of different strategies for domain adaptation in opinion mining0
Grammar Error Correction Using Pseudo-Error Sentences and Domain Adaptation0
Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation0
Graph-Based Cross-Domain Knowledge Distillation for Cross-Dataset Text-to-Image Person Retrieval0
Graph-Based Lexicon Expansion with Sparsity-Inducing Penalties0
Graph Domain Adaptation: A Generative View0
Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation0
Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation0
Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network0
Graph Domain Adaptation with Localized Graph Signal Representations0
Improving Cause-of-Death Classification from Verbal Autopsy Reports0
Evaluating the Learning Curve of Domain Adaptive Statistical Machine Translation Systems0
Improve Unsupervised Domain Adaptation with Mixup Training0
Evaluating the Impact of Using a Domain-specific Bilingual Lexicon on the Performance of a Hybrid Machine Translation Approach0
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning0
Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation0
Grasping Detection Network with Uncertainty Estimation for Confidence-Driven Semi-Supervised Domain Adaptation0
Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision0
Asymmetrical Latent Representation for Individual Treatment Effect Modeling0
Improved Techniques for Adversarial Discriminative Domain Adaptation0
Evaluating Domain Adaptation for Machine Translation Across Scenarios0
Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG0
GRU-AUNet: A Domain Adaptation Framework for Contactless Fingerprint Presentation Attack Detection0
DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptation0
DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception0
Domain Adaptive Medical Image Segmentation via Adversarial Learning of Disease-Specific Spatial Patterns0
Etude de diff\'erentes strat\'egies d'adaptation \`a un nouveau domaine en fouille d'opinion (Study of various strategies for adapting an opinion classifier to a new domain) [in French]0
Adversarially Trained Object Detector for Unsupervised Domain Adaptation0
Towards Understanding Domain Adapted Sentence Embeddings for Document Retrieval0
Improving Automated Program Repair with Domain Adaptation0
Improving Citation Polarity Classification with Product Reviews0
Improving Domain Adaptation for Machine Translation withTranslation Pieces0
Batch Group Normalization0
Hard Negative Mining for Metric Learning Based Zero-Shot Classification0
ETS: Domain Adaptation and Stacking for Short Answer Scoring0
Harmonization-enriched domain adaptation with light fine-tuning for multiple sclerosis lesion segmentation0
Batch weight for domain adaptation with mass shift0
Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data0
Hashing in the Zero Shot Framework with Domain Adaptation0
A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions0
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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
4CMKDAccuracy89Unverified
5PMTransAccuracy89Unverified
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
8DDAAccuracy88.9Unverified
9MEDMAccuracy88.9Unverified
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