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 42014250 of 6439 papers

TitleStatusHype
Adversarial Domain Adaptation for Action Recognition Around the Clock0
Adversarial Domain Adaptation for Cell Segmentation0
Adversarial Domain Adaptation for Machine Reading Comprehension0
Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data0
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces0
Adversarial Domain Adaptation for Stance Detection0
Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems0
Adversarial domain adaptation to reduce sample bias of a high energy physics classifier0
Adversarial Domain Adaptation Using Artificial Titles for Abstractive Title Generation0
Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices0
Adversarial Dropout Regularization0
Adversarial Dual Distinct Classifiers for Unsupervised Domain Adaptation0
Adversarial Inductive Transfer Learning with input and output space adaptation0
Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation0
Adversarial Learning for Zero-shot Domain Adaptation0
Adversarial Learning Networks: Source-free Unsupervised Domain Incremental Learning0
Adversarially Masked Video Consistency for Unsupervised Domain Adaptation0
Adversarially Trained Object Detector for Unsupervised Domain Adaptation0
Adversarial Multiple Source Domain Adaptation0
Adversarial Open Domain Adaption Framework (AODA): Sketch-to-Photo Synthesis0
Adversarial Network with Multiple Classifiers for Open Set Domain Adaptation0
Adversarial Robustness for Unsupervised Domain Adaptation0
Adversarial Sample Enhanced Domain Adaptation: A Case Study on Predictive Modeling with Electronic Health Records0
Adversarial Semi-Supervised Domain Adaptation for Semantic Segmentation: A New Role for Labeled Target Samples0
Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis0
Adversarial Support Alignment0
Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation0
Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis0
Adversarial Training for Cross-Domain Universal Dependency Parsing0
Adversarial Transfer of Pose Estimation Regression0
Adversarial Unsupervised Domain Adaptation for Harmonic-Percussive Source Separation0
Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection0
Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate0
Matching Embeddings for Domain Adaptation0
Adverse Weather Optical Flow: Cumulative Homogeneous-Heterogeneous Adaptation0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification0
AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation0
AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection0
Affine Transport for Sim-to-Real Domain Adaptation0
A Flexible Framework for Universal Computational Aberration Correction via Automatic Lens Library Generation and Domain Adaptation0
A Fourier Transform Framework for Domain Adaptation0
A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer0
A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data0
A Fully Convolutional Tri-branch Network (FCTN) for Domain Adaptation0
A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin0
Against Adversarial Learning: Naturally Distinguish Known and Unknown in Open Set Domain Adaptation0
Age and Gender Classification From Ear Images0
A general approach to bridge the reality-gap0
A General Approach to Domain Adaptation with Applications in Astronomy0
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation0
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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