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 40014050 of 6439 papers

TitleStatusHype
Towards Dynamic and Small Objects Refinement for Unsupervised Domain Adaptative Nighttime Semantic Segmentation0
Towards Explaining Expressive Qualities in Piano Recordings: Transfer of Explanatory Features via Acoustic Domain Adaptation0
Towards Fair Cross-Domain Adaptation via Generative Learning0
Towards Fair Knowledge Transfer for Imbalanced Domain Adaptation0
Towards Flow Graph Prediction of Open-Domain Procedural Texts0
Deep Inertial Navigation using Continuous Domain Adaptation and Optimal Transport0
Towards Learning free Naive Bayes Nearest Neighbor-based Domain Adaptation0
Towards Model Generalization for Monocular 3D Object Detection0
Towards Open-world Generalized Deepfake Detection: General Feature Extraction via Unsupervised Domain Adaptation0
Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation0
Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation0
Towards Principled Unsupervised Learning0
Towards Realizing the Value of Labeled Target Samples: a Two-Stage Approach for Semi-Supervised Domain Adaptation0
Towards Reducing Data Acquisition and Labeling for Defect Detection using Simulated Data0
Towards Robust 3D Object Recognition with Dense-to-Sparse Deep Domain Adaptation0
Towards Robust and Fair Vision Learning in Open-World Environments0
Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging0
Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal0
Towards Robust Online Domain Adaptive Semantic Segmentation under Adverse Weather Conditions0
Towards Scalable Topological Regularizers0
Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation0
Towards Semantic Search for Community Question Answering for Mortgage Officers0
Towards Shared Datasets for Normalization Research0
Towards Simple and Efficient Task-Adaptive Pre-training for Text Classification0
Towards Space Group Determination from EBSD Patterns: The Role of Deep Learning and High-throughput Dynamical Simulations0
Towards Spatially-Lucid AI Classification in Non-Euclidean Space: An Application for MxIF Oncology Data0
Towards Stable and Comprehensive Domain Alignment: Max-Margin Domain-Adversarial Training0
Towards Subject Agnostic Affective Emotion Recognition0
Towards Trustworthy Unsupervised Domain Adaptation: A Representation Learning Perspective for Enhancing Robustness, Discrimination, and Generalization0
Towards Understanding ASR Error Correction for Medical Conversations0
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation0
Towards Understanding the Role of Sharpness-Aware Minimization Algorithms for Out-of-Distribution Generalization0
Towards Unsupervised Domain Adaptation for Deep Face Recognition under Privacy Constraints via Federated Learning0
Towards Unsupervised Domain Adaptation via Domain-Transformer0
Towards Writing Style Adaptation in Handwriting Recognition0
Tracking by Instance Detection: A Meta-Learning Approach0
Filtering in tractography using autoencoders (FINTA)0
Traditional Chinese Parsing Evaluation at SIGHAN Bake-offs 20120
Training and Domain Adaptation for Supervised Text Segmentation0
Training-Free Model Merging for Multi-target Domain Adaptation0
Training Generative Adversarial Networks for Optical Property Mapping using Synthetic Image Data0
Towards Reusable Network Components by Learning Compatible Representations0
Training on Test Data with Bayesian Adaptation for Covariate Shift0
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction0
Transcending Controlled Environments Assessing the Transferability of ASRRobust NLU Models to Real-World Applications0
Transcending Domains through Text-to-Image Diffusion: A Source-Free Approach to Domain Adaptation0
Transducer Adaptive Ultrasound Volume Reconstruction0
Transductive Adaptation of Black Box Predictions0
Transductive Zero-Shot Learning with Adaptive Structural Embedding0
Transferability in Deep Learning: A Survey0
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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