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 53515400 of 6439 papers

TitleStatusHype
On L_2-consistency of nearest neighbor matching0
Adversarial Domain Adaptation for Stance Detection0
Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain AdaptationCode1
Agnostic Federated LearningCode1
Feature-Critic Networks for Heterogeneous Domain GeneralizationCode0
Multi-Task Deep Neural Networks for Natural Language UnderstandingCode0
Domain Discrepancy Measure for Complex Models in Unsupervised Domain Adaptation0
On Learning Invariant Representation for Domain AdaptationCode0
Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts0
Orthogonal Statistical LearningCode0
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image SegmentationCode1
Towards Compact ConvNets via Structure-Sparsity Regularized Filter PruningCode0
Domain Adaptation for sEMG-based Gesture Recognition with Recurrent Neural NetworksCode1
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift AdaptationCode1
Learning Generalizable and Identity-Discriminative Representations for Face Anti-SpoofingCode0
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving0
Truly Generalizable Radiograph Segmentation with Conditional Domain AdaptationCode0
Domain Adaptation for Structured Output via Discriminative Patch RepresentationsCode0
A review of domain adaptation without target labelsCode0
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene UnderstandingCode1
Contrastive Adaptation Network for Unsupervised Domain AdaptationCode1
On Minimum Discrepancy Estimation for Deep Domain AdaptationCode1
An introduction to domain adaptation and transfer learning0
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification0
EANet: Enhancing Alignment for Cross-Domain Person Re-identificationCode0
Artistic Object Recognition by Unsupervised Style Adaptation0
The CORAL+ Algorithm for Unsupervised Domain Adaptation of PLDA0
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban ScenesCode1
Multi-component Image Translation for Deep Domain Generalization0
Patent Retrieval: A Literature Review0
A General Approach to Domain Adaptation with Applications in Astronomy0
PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac SegmentationCode0
Cross-Database Micro-Expression Recognition: A Benchmark0
TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation0
Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks0
Domain Adaptation for Reinforcement Learning on the Atari0
Domain Adaptation on Graphs by Learning Graph Topologies: Theoretical Analysis and an Algorithm0
PAC Learning Guarantees Under Covariate Shift0
A Parametric Top-View Representation of Complex Road Scenes0
DLOW: Domain Flow for Adaptation and GeneralizationCode0
The Global Anchor Method for Quantifying Linguistic Shifts and Domain AdaptationCode0
Attentional Road Safety Networks0
Multichannel Semantic Segmentation with Unsupervised Domain AdaptationCode0
Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models0
What is the Effect of Importance Weighting in Deep Learning?Code0
ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection0
Disjoint Label Space Transfer Learning with Common Factorised Space0
A novel health risk model based on intraday physical activity time series collected by smartphones0
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation0
A Survey of Unsupervised Deep Domain AdaptationCode0
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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
4CMKDAccuracy89Unverified
5PMTransAccuracy89Unverified
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
8DDAAccuracy88.9Unverified
9MEDMAccuracy88.9Unverified
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