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 31513200 of 6439 papers

TitleStatusHype
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources0
Towards Low-Cost and Efficient Malaria DetectionCode0
Contrastive Vicinal Space for Unsupervised Domain AdaptationCode1
Clustering Effect of (Linearized) Adversarial Robust ModelsCode0
Cross-Domain Adaptive Teacher for Object DetectionCode1
Exploiting Both Domain-specific and Invariant Knowledge via a Win-win Transformer for Unsupervised Domain Adaptation0
Temporal Effects on Pre-trained Models for Language Processing TasksCode0
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive LearningCode1
UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation0
Source-free unsupervised domain adaptation for cross-modality abdominal multi-organ segmentationCode1
Unsupervised cross domain learning with applications to 7 layer segmentation of OCTs0
Lifting 2D Human Pose to 3D with Domain Adapted 3D Body Concept0
Self-Supervised Pre-Training for Transformer-Based Person Re-IdentificationCode1
Reinforcement Learning for Few-Shot Text Generation AdaptationCode0
DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing0
Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability0
Unsupervised Domain Adaptation for RF-based Gesture Recognition0
Progressive learning with multi-scale attention network for cross-domain vehicle re-identification0
Deep Domain Adaptation for Pavement Crack Detection0
Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning0
Merging Models with Fisher-Weighted AveragingCode1
Boosting Supervised Learning Performance with Co-training0
One-Shot Generative Domain Adaptation0
Edge-preserving Domain Adaptation for semantic segmentation of Medical Images0
See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain AdaptationCode1
Cryo-shift: Reducing domain shift in cryo-electron subtomograms with unsupervised domain adaptation and randomization0
QA Domain Adaptation using Data Augmentation and Contrastive Adaptation0
Learning to Learn Recognising Biomedical Entities from Multiple Domains with Task Hardness0
Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration0
Unsupervised Domain Adaptation with Contrastive Learning for Cross-domain Chinese NER0
Revisiting Softmax for Uncertainty Approximation in Text Classification0
End-to-end Task-oriented Dialog Policy Learning based on Pre-trained Language Model0
Unsupervised Domain Adaptation for Event Detection via Meta Self-Paced Learning0
ECSpell^UD: Zero-shot Domain Adaptive Chinese Spelling Check with User Dictionary0
A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language Models0
DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation0
Building Chinese Biomedical Language Models via Multi-Level Text DiscriminationCode0
Incorporating Multiple Knowledge Sources for Targeted Aspect-based Financial Sentiment Analysis0
Non-Parametric Domain Adaptation for End-to-End Speech Translation0
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error0
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER0
Modular Domain Adaptation0
Synthetic Question Value Estimation for Domain Adaptation of Question Answering0
Cost-Effective Training in Low-Resource Neural Machine Translation0
Towards a Fine-Grained Multi-Domain Neural Machine Translation Using Inter-Domain Relationships0
KALA: Knowledge-Augmented Language Model Adaptation0
Causal Effect Variational Autoencoder with Uniform Treatment0
On-Demand Unlabeled Personalized Federated Learning0
Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation0
HLT-NUS SUBMISSION FOR 2020 NIST Conversational Telephone Speech SRECode1
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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