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 19512000 of 6439 papers

TitleStatusHype
A Two Stage Adaptation Framework for Frame Detection via Prompt LearningCode0
Co-Teaching for Unsupervised Domain Adaptation and ExpansionCode0
Adapting Pretrained Language Models for Solving Tabular Prediction Problems in the Electronic Health RecordCode0
Attract or Distract: Exploit the Margin of Open SetCode0
Generalizing A Person Retrieval Model Hetero- and HomogeneouslyCode0
Generalizing Segmentation Foundation Model Under Sim-to-real Domain-shift for Guidewire Segmentation in X-ray FluoroscopyCode0
Cost-effective Framework for Gradual Domain Adaptation with MultifidelityCode0
COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised LearningCode0
Co-STAR: Collaborative Curriculum Self-Training with Adaptive Regularization for Source-Free Video Domain AdaptationCode0
3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit ModelsCode0
Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for HistologyCode0
COSMo: CLIP Talks on Open-Set Multi-Target Domain AdaptationCode0
Generalizing Across Domains via Cross-Gradient TrainingCode0
Generative Pseudo-label Refinement for Unsupervised Domain AdaptationCode0
Generalizable Image Repair for Robust Visual Autonomous RacingCode0
Correlation Alignment by Riemannian Metric for Domain AdaptationCode0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
General Frameworks for Conditional Two-Sample TestingCode0
Adapting Object Detectors via Selective Cross-Domain AlignmentCode0
General Domain Adaptation Through Proportional Progressive Pseudo LabelingCode0
Generalization Enhancement Strategies to Enable Cross-year Cropland Mapping with Convolutional Neural Networks Trained Using Historical SamplesCode0
Source-Guided Similarity Preservation for Online Person Re-IdentificationCode0
Attention-based Domain Adaptation Forecasting of Streamflow in Data-Sparse RegionsCode0
Gaze360: Physically Unconstrained Gaze Estimation in the WildCode0
Adversarial Semantic Hallucination for Domain Generalized Semantic SegmentationCode0
CORE-ReID V2: Advancing the Domain Adaptation for Object Re-Identification with Optimized Training and Ensemble FusionCode0
GCAL: Adapting Graph Models to Evolving Domain ShiftsCode0
Class Overwhelms: Mutual Conditional Blended-Target Domain AdaptationCode0
Attention-based Class-Conditioned Alignment for Multi-Source Domain Adaptation of Object DetectorsCode0
FusDom: Combining In-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised LearningCode0
Adapting Neural Architectures Between DomainsCode0
CoReD: Generalizing Fake Media Detection with Continual Representation using DistillationCode0
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain AdaptationCode0
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical NeuroscienceCode0
From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine TranslationCode0
From Third Person to First Person: Dataset and Baselines for Synthesis and RetrievalCode0
Attending to Discriminative Certainty for Domain AdaptationCode0
From Galaxy Zoo DECaLS to BASS/MzLS: detailed galaxy morphology classification with unsupervised domain adaptionCode0
From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain AdaptationCode0
Cooperative Distribution Alignment via JSD Upper BoundCode0
ATL: Autonomous Knowledge Transfer from Many Streaming ProcessesCode0
Convolutional Monge Mapping Normalization for learning on sleep dataCode0
From Colors to Classes: Emergence of Concepts in Vision TransformersCode0
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random SelectionCode0
An Unsupervised Neural Attention Model for Aspect ExtractionCode0
FreSaDa: A French Satire Data Set for Cross-Domain Satire DetectionCode0
FreqAlign: Excavating Perception-oriented Transferability for Blind Image Quality Assessment from A Frequency PerspectiveCode0
Statistical Inference for Sequential Feature Selection after Domain AdaptationCode0
From Forest to Zoo: Great Ape Behavior Recognition with ChimpBehaveCode0
FogGuard: guarding YOLO against fog using perceptual lossCode0
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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