SOTAVerified

Source-Free Domain Adaptation

Source-Free Domain Adaptation (SFDA) is a domain adaptation method in machine learning and computer vision where the goal is to adapt a pre-trained model to a new, target domain without access to the source domain data. This approach is advantageous in scenarios where sharing the source data is impractical due to privacy concerns, data size, or proprietary restrictions

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–188 of 188 papers

TitleStatusHype
Source-Free Video Domain Adaptation With Spatial-Temporal-Historical Consistency Learning—0
A Comparison of Strategies for Source-Free Domain Adaptation—0
A Chebyshev Confidence Guided Source-Free Domain Adaptation Framework for Medical Image Segmentation—0
Chaos to Order: A Label Propagation Perspective on Source-Free Domain Adaptation—0
ViLAaD: Enhancing "Attracting and Dispersing'' Source-Free Domain Adaptation with Vision-and-Language Model—0
Target-agnostic Source-free Domain Adaptation for Regression Tasks—0
TempT: Temporal consistency for Test-time adaptation—0
Test-Time Adaptation for Visual Document Understanding—0
Test-time Batch Statistics Calibration for Covariate Shift—0
The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation—0
When Source-Free Domain Adaptation Meets Learning with Noisy Labels—0
Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation—0
Cleaning Noisy Labels by Negative Ensemble Learning for Source-Free Unsupervised Domain Adaptation—0
Label Calibration in Source Free Domain Adaptation—0
BLCUFIGHT at SemEval-2021 Task 10: Novel Unsupervised Frameworks For Source-Free Domain Adaptation—0
Local-Global Pseudo-label Correction for Source-free Domain Adaptive Medical Image Segmentation—0
Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification—0
Low Saturation Confidence Distribution-based Test-Time Adaptation for Cross-Domain Remote Sensing Image Classification—0
MedAI at SemEval-2021 Task 10: Negation-aware Pre-training for Source-free Negation Detection Domain Adaptation—0
MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation—0
MTLoc: A Confidence-Based Source-Free Domain Adaptation Approach For Indoor Localization—0
Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation—0
Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation—0
Transcending Domains through Text-to-Image Diffusion: A Source-Free Approach to Domain Adaptation—0
Selection, Ensemble, and Adaptation: Advancing Multi-Source-Free Domain Adaptation via Architecture Zoo—0
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets—0
Better Practices for Domain Adaptation—0
Prior-guided Source-free Domain Adaptation for Human Pose Estimation—0
Probability Distribution Alignment and Low-Rank Weight Decomposition for Source-Free Domain Adaptive Brain Decoding—0
Jacobian Norm for Unsupervised Source-Free Domain Adaptation—0
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering—0
In Search for a Generalizable Method for Source Free Domain Adaptation—0
Improving Online Source-free Domain Adaptation for Object Detection by Unsupervised Data Acquisition—0
Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation—0
Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment—0
Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data—0
Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety—0
IITK at SemEval-2021 Task 10: Source-Free Unsupervised Domain Adaptation using Class Prototypes—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RCLAccuracy93.2—Unverified
2SFDA2++Accuracy89.6—Unverified
3SPMAccuracy89.4—Unverified
4SFDA2Accuracy88.1—Unverified
5C-SFDAAccuracy87.8—Unverified
6DaCAccuracy87.3—Unverified
7SHOT++Accuracy87.3—Unverified
8NRCAccuracy85.9—Unverified
9G-SFDAAccuracy85.4—Unverified
10SHOTAccuracy82.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SPMAverage Accuracy86.7—Unverified
2DRAAverage Accuracy84—Unverified
3NELAverage Accuracy72.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CMAmIoU69.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CMAmIoU53.6—Unverified