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

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Showing 1151–1200 of 6439 papers

TitleStatusHype
Real-World Atmospheric Turbulence Correction via Domain Adaptation—0
Domain Adaptation Using Pseudo Labels—0
Multi-source-free Domain Adaptation via Uncertainty-aware Adaptive DistillationCode0
ControlUDA: Controllable Diffusion-assisted Unsupervised Domain Adaptation for Cross-Weather Semantic Segmentation—0
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free InferenceCode1
DAPlankton: Benchmark Dataset for Multi-instrument Plankton Recognition via Fine-grained Domain Adaptation—0
Rethinking Propagation for Unsupervised Graph Domain AdaptationCode1
Progressive unsupervised domain adaptation for ASR using ensemble models and multi-stage training—0
Source-Free Domain Adaptation with Diffusion-Guided Source Data Generation—0
Progressive Conservative Adaptation for Evolving Target Domains—0
ConvLoRA and AdaBN based Domain Adaptation via Self-TrainingCode2
Energy-based Domain-Adaptive Segmentation with Depth Guidance—0
Continual Domain Adversarial Adaptation via Double-Head Discriminators—0
Test-Time Adaptation for Depth CompletionCode1
AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution ImageCode0
Domain Adaptation of Multilingual Semantic Search - Literature Review—0
EMN: Brain-inspired Elastic Memory Network for Quick Domain Adaptive Feature Mapping—0
From Synthetic to Real: Unveiling the Power of Synthetic Data for Video Person Re-ID—0
On f-Divergence Principled Domain Adaptation: An Improved FrameworkCode0
Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challengeCode0
AGILE: Approach-based Grasp Inference Learned from Element Decomposition—0
Source-Free Unsupervised Domain Adaptation with Hypothesis Consolidation of Prediction RationaleCode0
Credal Learning Theory—0
Graph Domain Adaptation: Challenges, Progress and ProspectsCode2
Getting the most out of your tokenizer for pre-training and domain adaptationCode1
We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation BaselineCode1
How Useful is Continued Pre-Training for Generative Unsupervised Domain Adaptation?—0
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow—0
Continuous Unsupervised Domain Adaptation Using Stabilized Representations and Experience ReplayCode0
Source-free Domain Adaptive Object Detection in Remote Sensing Images—0
COMET: Contrastive Mean Teacher for Online Source-Free Universal Domain AdaptationCode0
A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation—0
Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data—0
cantnlp@LT-EDI-2024: Automatic Detection of Anti-LGBTQ+ Hate Speech in Under-resourced Languages—0
An Empirical Investigation of Domain Adaptation Ability for Chinese Spelling Check Models—0
UNIT-DSR: Dysarthric Speech Reconstruction System Using Speech Unit Normalization—0
Resilient Practical Test-Time Adaptation: Soft Batch Normalization Alignment and Entropy-driven Memory Bank—0
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement LearningCode0
CNG-SFDA:Clean-and-Noisy Region Guided Online-Offline Source-Free Domain AdaptationCode0
Language Modelling Approaches to Adaptive Machine Translation—0
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain AbstractionCode0
LanDA: Language-Guided Multi-Source Domain Adaptation—0
Weakly supervised covariance matrices alignment through Stiefel matrices estimation for MEG applications—0
Finetuning Foundation Models for Joint Analysis Optimization—0
LightSleepNet: Design of a Personalized Portable Sleep Staging System Based on Single-Channel EEG—0
Enhancing cross-domain detection: adaptive class-aware contrastive transformer—0
Uncertainty-Guided Alignment for Unsupervised Domain Adaptation in Regression—0
AdCorDA: Classifier Refinement via Adversarial Correction and Domain Adaptation—0
UniHDA: A Unified and Versatile Framework for Multi-Modal Hybrid Domain Adaptation—0
AdaEmbed: Semi-supervised Domain Adaptation in the Embedding Space—0
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All datasetsOffice-31SYNTHIA-to-CityscapesGTA5 to CityscapesOffice-HomeVisDA2017ImageCLEF-DACityscapes to ACDCMNIST-to-USPSSVHN-to-MNISTUSPS-to-MNISTSVNH-to-MNISTMoLane

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FFTATAverage Accuracy96—Unverified
2PMTransAverage Accuracy95.3—Unverified
3CMKDAverage Accuracy94.4—Unverified
4SSRT-B (ours)Average Accuracy93.5—Unverified
5CDTransAverage Accuracy92.6—Unverified
6CoViAverage Accuracy91.8—Unverified
7GSDEAverage Accuracy91.7—Unverified
8FixBiAverage Accuracy91.4—Unverified
9Contrastive Adaptation NetworkAverage Accuracy90.6—Unverified
10BIWAAAverage Accuracy90.5—Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU78.1—Unverified
2ILM-ASSLmIoU76.6—Unverified
3DCFmIoU69.3—Unverified
4HRDA+PiPamIoU68.2—Unverified
5MICmIoU67.3—Unverified
6FREDOM - TransformermIoU67—Unverified
7HRDAmIoU65.8—Unverified
8SePiComIoU64.3—Unverified
9MIC + Guidance TrainingmIoU63.8—Unverified
10DAFormer + ProCSTmIoU61.6—Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU77.8—Unverified
2DCFmIoU77.7—Unverified
3ILM-ASSLmIoU76.1—Unverified
4MICmIoU75.9—Unverified
5HRDA+PiPamIoU75.6—Unverified
6HRDAmIoU73.8—Unverified
7FREDOM - TransformermIoU73.6—Unverified
8HALOmIoU73.3—Unverified
9SePiComIoU70.3—Unverified
10DAFormer + ProCSTmIoU69.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SWGAccuracy92.3—Unverified
2RCLAccuracy90—Unverified
3PGA (ViT-L/14)Accuracy89.4—Unverified
4CMKDAccuracy89—Unverified
5PMTransAccuracy89—Unverified
6MICAccuracy86.2—Unverified
7PGA (ViT-B/16)Accuracy85.1—Unverified
8ELSAccuracy84.6—Unverified
9SDAT (ViT-B/16)Accuracy84.3—Unverified
10CDTrans (DeiT-B)Accuracy80.5—Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy93.8—Unverified
2RCLAccuracy93.2—Unverified
3MICAccuracy92.8—Unverified
4SWGAccuracy92.7—Unverified
5CMKDAccuracy91.8—Unverified
6DePTAccuracy90.7—Unverified
7SDAT(ViT)Accuracy89.8—Unverified
8SFDA2++Accuracy89.6—Unverified
9PMtransAccuracy88.8—Unverified
10CoViAccuracy88.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CMKDAccuracy94.3—Unverified
2MCC+NWDAccuracy90.7—Unverified
3GLOT-DRAccuracy90.4—Unverified
4SPLAccuracy90.3—Unverified
5DFA-SAFNAccuracy90.2—Unverified
6DADAAccuracy89.3—Unverified
7DFA-ENTAccuracy89.1—Unverified
8DDAAccuracy88.9—Unverified
9MEDMAccuracy88.9—Unverified
10IAFN+ENTAccuracy88.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SoRAmIoU78.8—Unverified
2ReinmIoU77.6—Unverified
3CoDAmIoU72.6—Unverified
4Refign (HRDA)mIoU72.1—Unverified
5HALOmIoU71.9—Unverified
6MICmIoU70.4—Unverified
7HRDAmIoU68—Unverified
8Refign (DAFormer)mIoU65.5—Unverified
9VBLC (DAFormer)mIoU64.2—Unverified
10CMFormermIoU60.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FACTAccuracy98.8—Unverified
2FAMCDAccuracy98.72—Unverified
3DFA-MCDAccuracy98.6—Unverified
4Mean teacherAccuracy98.26—Unverified
5DRANetAccuracy98.2—Unverified
6SHOTAccuracy98—Unverified
7DFA-ENTAccuracy97.9—Unverified
8CyCleGAN (Light-weight Calibrator)Accuracy97.1—Unverified