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 32013250 of 6439 papers

TitleStatusHype
Source-Free Unsupervised Domain Adaptation with Norm and Shape Constraints for Medical Image Segmentation0
Domain Adaptation from ScratchCode0
Low Resource Chat Translation: A Benchmark for Hindi–English Language PairCode0
Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation0
User Satisfaction Modeling with Domain Adaptation in Task-oriented Dialogue Systems0
Improving Translation of Out Of Vocabulary Words using Bilingual Lexicon Induction in Low-Resource Machine Translation0
Unsupervised Domain Adaptation on Question-Answering System with Conversation Data0
Feature Alignment by Uncertainty and Self-Training for Source-Free Unsupervised Domain Adaptation0
AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection0
Segmentation-guided Domain Adaptation and Data Harmonization of Multi-device Retinal Optical Coherence Tomography using Cycle-Consistent Generative Adversarial Networks0
Transfering Low-Frequency Features for Domain Adaptation0
Few-shot Adaptive Object Detection with Cross-Domain CutMix0
Super-model ecosystem: A domain-adaptation perspective0
Latent Covariate Shift: Unlocking Partial Identifiability for Multi-Source Domain Adaptation0
Radial Prediction Domain Adaption Classifier for the MIDOG 2022 ChallengeCode0
Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution dataCode0
Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model0
Multi-Scale Multi-Target Domain Adaptation for Angle Closure Classification0
A Compact Pretraining Approach for Neural Language ModelsCode0
Image Based Food Energy Estimation With Depth Domain Adaptation0
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network0
IMPaSh: A Novel Domain-shift Resistant Representation for Colorectal Cancer Tissue ClassificationCode0
Consistency Regularization for Domain AdaptationCode0
RAIN: RegulArization on Input and Network for Black-Box Domain AdaptationCode0
MentorGNN: Deriving Curriculum for Pre-Training GNNsCode0
Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19Code0
Test-time Training for Data-efficient UCDRCode0
A physics-based domain adaptation framework for modelling and forecasting building energy systems0
Effective Transfer Learning for Low-Resource Natural Language Understanding0
ModSelect: Automatic Modality Selection for Synthetic-to-Real Domain Generalization0
Cross-Domain Evaluation of a Deep Learning-Based Type Inference SystemCode0
Domain Camera Adaptation and Collaborative Multiple Feature Clustering for Unsupervised Person Re-ID0
Semi-supervised domain adaptation with CycleGAN guided by a downstream task loss0
Cross-Domain Few-Shot Classification via Inter-Source Stylization0
LAMA-Net: Unsupervised Domain Adaptation via Latent Alignment and Manifold Learning for RUL Prediction0
Summarizing Patients Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models0
ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation0
Unsupervised Domain Adaptation for Segmentation with Black-box Source Model0
Introducing Intermediate Domains for Effective Self-Training during Test-Time0
Subtype-Aware Dynamic Unsupervised Domain Adaptation0
Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives0
Combating Label Distribution Shift for Active Domain Adaptation0
Learning to Infer Counterfactuals: Meta-Learning for Estimating Multiple Imbalanced Treatment Effects0
Memory Efficient Temporal & Visual Graph Model for Unsupervised Video Domain Adaptation0
Automated Utterance Labeling of Conversations Using Natural Language ProcessingCode0
Continual Unsupervised Domain Adaptation for Semantic Segmentation using a Class-Specific Transfer0
Domain-invariant Prototypes for Semantic Segmentation0
Private Domain Adaptation from a Public Source0
Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation0
Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction0
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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