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 50015050 of 6439 papers

TitleStatusHype
Node-Adapt, Path-Adapt and Tree-Adapt:Model-Transfer Domain Adaptation for Random Forest0
Noise Optimized Conditional Diffusion for Domain Adaptation0
Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis0
Non-Linear Domain Adaptation with Boosting0
Nonlinear Embedding Transform for Unsupervised Domain Adaptation0
Non-Parametric Adaptation for Neural Machine Translation0
Non-Parametric Domain Adaptation for End-to-End Speech Translation0
Non-Reference Quality Assessment for Medical Imaging: Application to Synthetic Brain MRIs0
No-reference Screen Content Image Quality Assessment with Unsupervised Domain Adaptation0
Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation0
NRC Machine Translation System for WMT 20170
NTT's Machine Translation Systems for WMT19 Robustness Task0
NTU-1 at SemEval-2017 Task 12: Detection and classification of temporal events in clinical data with domain adaptation0
Object-based (yet Class-agnostic) Video Domain Adaptation0
Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques0
Observations on LLMs for Telecom Domain: Capabilities and Limitations0
ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition0
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation0
On Causality in Domain Adaptation and Semi-Supervised Learning: an Information-Theoretic Analysis for Parametric Models0
On Correlating Factors for Domain Adaptation Performance0
ONDA-Pose: Occlusion-Aware Neural Domain Adaptation for Self-Supervised 6D Object Pose Estimation0
On-Device Domain Learning for Keyword Spotting on Low-Power Extreme Edge Embedded Systems0
On-Device Self-Supervised Learning of Low-Latency Monocular Depth from Only Events0
On Direct Distribution Matching for Adapting Segmentation Networks0
On Domain-Specific Post-Training for Multimodal Large Language Models0
One-bit Supervision for Image Classification: Problem, Solution, and Beyond0
One-Class Domain Adaptation via Meta-Learning0
One model per entity: using hundreds of machine learning models to recognize and normalize biomedical names in text0
One-Shot Adaptation of Supervised Deep Convolutional Models0
One-Shot Domain Adaptation For Face Generation0
One-shot domain adaptation for semantic face editing of real world images using StyleALAE0
One-Shot Domain Adaptive and Generalizable Semantic Segmentation with Class-Aware Cross-Domain Transformers0
One-Shot Federated Unsupervised Domain Adaptation with Scaled Entropy Attention and Multi-Source Smoothed Pseudo Labeling0
One-Shot Generative Domain Adaptation0
One-Shot Learning for Periocular Recognition: Exploring the Effect of Domain Adaptation and Data Bias on Deep Representations0
One-Shot Neural Architecture Search with Network Similarity Directed Initialization for Pathological Image Classification0
On Evolving Attention Towards Domain Adaptation0
On Fine-Tuned Deep Features for Unsupervised Domain Adaptation0
On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering0
On Instruction-Finetuning Neural Machine Translation Models0
On Label Shift in Domain Adaptation via Wasserstein Distance0
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources0
Online Active Learning for Cost Sensitive Domain Adaptation0
Online and Offline Domain Adaptation for Reducing BCI Calibration Effort0
Online Domain Adaptation for Continuous Cross-Subject Liver Viability Evaluation Based on Irregular Thermal Data0
Online Domain Adaptation for Multi-Object Tracking0
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation0
Online Multi-Source Domain Adaptation through Gaussian Mixtures and Dataset Dictionary Learning0
Online Unsupervised Domain Adaptation for Person Re-identification0
Online Updating of Word Representations for Part-of-Speech Tagging0
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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