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 51100 of 6439 papers

TitleStatusHype
EgoVideo: Exploring Egocentric Foundation Model and Downstream AdaptationCode2
UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of RerankersCode2
Domain Adaptation with a Single Vision-Language EmbeddingCode2
SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain Generalizable Representation LearningCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
HyperGAN-CLIP: A Unified Framework for Domain Adaptation, Image Synthesis and ManipulationCode2
Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic DataCode2
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic SegmentationCode2
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future DirectionsCode2
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image SegmentationCode2
AutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised LearningCode2
Anomaly Detection with Conditioned Denoising Diffusion ModelsCode2
Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain AdaptationCode2
Continual Test-Time Domain AdaptationCode2
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
CodeS: Towards Building Open-source Language Models for Text-to-SQLCode2
Adversarial Open Domain Adaptation for Sketch-to-Photo SynthesisCode2
ConvLoRA and AdaBN based Domain Adaptation via Self-TrainingCode2
Curvature Diversity-Driven Deformation and Domain Alignment for Point CloudCode2
DATR: Unsupervised Domain Adaptive Detection Transformer with Dataset-Level Adaptation and Prototypical AlignmentCode2
Denoising as Adaptation: Noise-Space Domain Adaptation for Image RestorationCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
Implicit Neural Representation in Medical Imaging: A Comparative SurveyCode2
Test-Time Domain Generalization via Universe Learning: A Multi-Graph Matching Approach for Medical Image SegmentationCode2
Foundational Large Language Models for Materials ResearchCode2
A Closer Look at Smoothness in Domain Adversarial TrainingCode1
Adversarial Bipartite Graph Learning for Video Domain AdaptationCode1
Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification and BeyondCode1
Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center DatasetCode1
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic SegmentationCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain AdaptationCode1
Adjustment and Alignment for Unbiased Open Set Domain AdaptationCode1
Adversarial Continual Learning for Multi-Domain Hippocampal SegmentationCode1
Domain Adaptation of Neural Machine Translation by Lexicon InductionCode1
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution GeneralizationCode1
A DIRT-T Approach to Unsupervised Domain AdaptationCode1
Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object DetectionCode1
Audio-Adaptive Activity Recognition Across Video DomainsCode1
A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language ModelsCode1
A Broad Study of Pre-training for Domain Generalization and AdaptationCode1
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation ModelsCode1
A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceCode1
Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram SynthesisCode1
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic SegmentationCode1
A Survey of World Models for Autonomous DrivingCode1
Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph LearningCode1
A Prototype-Oriented Framework for Unsupervised Domain AdaptationCode1
A Sensor Agnostic Domain Generalization Framework for Leveraging Geospatial Foundation Models: Enhancing Semantic Segmentation viaSynergistic Pseudo-Labeling and Generative LearningCode1
AD-CLIP: Adapting Domains in Prompt Space Using CLIPCode1
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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