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 61516200 of 6439 papers

TitleStatusHype
Large-scale ASR Domain Adaptation using Self- and Semi-supervised Learning0
Large-Scale Domain Adaptation via Teacher-Student Learning0
Large Scale Optimal Transport and Mapping Estimation0
Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency0
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning0
Large SMT data-sets extracted from Wikipedia0
Latent Alignment with Deep Set EEG Decoders0
Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition0
Latent Domain Learning with Dynamic Residual Adapters0
Latent Domain Phrase-based Models for Adaptation0
Latin-Spanish Neural Machine Translation: from the Bible to Saint Augustine0
Layer-wise Model Merging for Unsupervised Domain Adaptation in Segmentation Tasks0
Learn2Weight: Weights Transfer Defense against Similar-domain Adversarial Attacks0
Learn by Guessing: Multi-Step Pseudo-Label Refinement for Person Re-Identification0
Learning Adaptive Dense Event Stereo From the Image Domain0
Learning a Domain-Agnostic Visual Representation for Autonomous Driving via Contrastive Loss0
Learning a Domain-Invariant Embedding for Unsupervised Domain Adaptation Using Class-Conditioned Distribution Alignment0
Learning Agile Robotic Locomotion Skills by Imitating Animals0
Learning a Max-Margin Classifier for Cross-Domain Sentiment Analysis0
Learning and Deploying Robust Locomotion Policies with Minimal Dynamics Randomization0
Learning and Generalization with Mixture Data0
Learning an Invariant Hilbert Space for Domain Adaptation0
Learning a Phrase-based Translation Model from Monolingual Data with Application to Domain Adaptation0
Learning a POS tagger for AAVE-like language0
Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation0
Learning Bounds for Domain Adaptation0
On generalization in moment-based domain adaptation0
Learning by Grouping: A Multilevel Optimization Framework for Improving Fairness in Classification without Losing Accuracy0
Learning by Ignoring, with Application to Domain Adaptation0
Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation0
Learning Causal Representation for Training Cross-Domain Pose Estimator via Generative Interventions0
Learning causal representations for robust domain adaptation0
Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation0
Learning Compositional Representations for Effective Low-Shot Generalization0
Learning Compositional Transferability of Time Series for Source-Free Domain Adaptation0
Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation0
Learning Cross-Domain Landmarks for Heterogeneous Domain Adaptation0
Learning Cross-domain Semantic-Visual Relationships for Transductive Zero-Shot Learning0
Learning Cross-modal Contrastive Features for Video Domain Adaptation0
Learning Deep Features for Shape Correspondence with Domain Invariance0
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach0
Learning Domain Adaptive Features with Unlabeled Domain Bridges0
Learning domain-invariant classifiers for infant cry sounds0
Learning Domain-Invariant Features for Out-of-Context News Detection0
Learning Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation with Few Labeled Source Samples0
Learning Efficient Dialogue Policy from Demonstrations through Shaping0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding0
Learning Factorized Representations for Open-set Domain Adaptation0
Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation0
Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts0
Show:102550
← PrevPage 124 of 129Next →

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