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 51015150 of 6439 papers

TitleStatusHype
Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection0
Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation0
Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation0
Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data0
Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data0
Self-Adaptation for Unsupervised Domain Adaptation0
Opinions Summarization: Aspect Similarity Recognition Relaxes The Constraint of Predefined Aspects0
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment ClassificationCode0
Texture Underfitting for Domain Adaptation0
Unsupervised Domain Adaptation for Cross-sensor Pore Detection in High-resolution Fingerprint ImagesCode0
Data Augmentation with Atomic Templates for Spoken Language UnderstandingCode0
Heterogeneous Domain Adaptation via Soft Transfer Network0
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning0
VAE-based Domain Adaptation for Speaker Verification0
Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature EmbeddingsCode0
Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation0
Unsupervised Domain-Adaptive Person Re-identification Based on Attributes0
Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial ApproachCode0
Revisiting Simple Domain Adaptation Methods in Unsupervised Neural Machine Translation0
Domain Adaptive Text Style TransferCode0
Adversarial Domain Adaptation for Machine Reading Comprehension0
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant LearningCode0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning0
Preserving Semantic and Temporal Consistency for Unpaired Video-to-Video Translation0
Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation0
TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays0
Efficient Deep Neural Networks0
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning0
Cross-Domain Adaptation for Animal Pose Estimation0
Shallow Domain Adaptive Embeddings for Sentiment Analysis0
Task-Assisted Domain Adaptation with Anchor Tasks0
Knowledge distillation for semi-supervised domain adaptation0
Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain AdaptationCode0
UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task DistillationCode0
Constrained domain adaptation for Image segmentationCode0
Learning Vision-based Flight in Drone Swarms by Imitation0
Attract or Distract: Exploit the Margin of Open SetCode0
Image to Video Domain Adaptation Using Web Supervision0
Cross-lingual Text-independent Speaker Verification using Unsupervised Adversarial Discriminative Domain Adaptation0
Semi-supervised representation learning via dual autoencoders for domain adaptationCode0
Pseudo-Labeling Curriculum for Unsupervised Domain Adaptation0
Domain Adaptation for MT: A Study with Unknown and Out-of-Domain Tasks0
Huawei's NMT Systems for the WMT 2019 Biomedical Translation Task0
Baidu Neural Machine Translation Systems for WMT190
Improving Domain Adaptation for Machine Translation withTranslation Pieces0
The MLLP-UPV Supervised Machine Translation Systems for WMT19 News Translation Task0
APE through Neural and Statistical MT with Augmented Data. ADAPT/DCU Submission to the WMT 2019 APE Shared Task0
The MLLP-UPV Spanish-Portuguese and Portuguese-Spanish Machine Translation Systems for WMT19 Similar Language Translation Task0
Learning to Adapt Invariance in Memory for Person Re-identification0
Incremental Domain Adaptation for Neural Machine Translation in Low-Resource SettingsCode0
Show:102550
← PrevPage 103 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