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 54015450 of 6439 papers

TitleStatusHype
Moment Matching for Multi-Source Domain AdaptationCode0
Domain-Adaptive Single-View 3D ReconstructionCode0
Transferable Natural Language Interface to Structured Queries aided by Adversarial Generation0
Towards Continuous Domain adaptation for Healthcare0
CRAVES: Controlling Robotic Arm with a Vision-based Economic SystemCode0
Domain Alignment with Triplets0
Adversarial Domain Randomization0
SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection0
Unsupervised Domain Adaptation using Generative Models and Self-ensembling0
Regularized Wasserstein Means for Aligning Distributional DataCode1
ECO: Egocentric Cognitive Mapping0
Effectiveness of Domain Adaptation in Japanese Predicate-Argument Structure Analysis0
Domain Adaptation Using a Combination of Multiple Embeddings for Sentiment Analysis0
Osaka University MT Systems for WAT 2018: Rewarding, Preordering, and Domain Adaptation0
Domain Adaptation for Sentiment Analysis using Keywords in the Target Domain as the Learning Weight0
Extracting Relationships by Multi-Domain MatchingCode0
Revisiting ( , , )-similarity learning for domain adaptation0
Adversarial Multiple Source Domain Adaptation0
From Third Person to First Person: Dataset and Baselines for Synthesis and RetrievalCode0
Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation NetworkCode1
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic SegmentationCode1
Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption0
Face Detection in the Operating Room: Comparison of State-of-the-art Methods and a Self-supervised Approach0
Identity Preserving Generative Adversarial Network for Cross-Domain Person Re-identification0
Part-level Car Parsing and Reconstruction from Single Street View0
GANtruth - an unpaired image-to-image translation method for driving scenarios0
IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained EnvironmentsCode0
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identificationCode0
Universal Semi-Supervised Semantic SegmentationCode0
Robustness against the channel effect in pathological voice detection0
Similarity-preserving Image-image Domain Adaptation for Person Re-identification0
Efficient Structured Pruning and Architecture Searching for Group ConvolutionCode0
Progressive Feature Alignment for Unsupervised Domain Adaptation0
Population-aware Hierarchical Bayesian Domain Adaptation0
Understanding and Measuring Psychological Stress using Social MediaCode0
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain AdaptationCode0
Deep Discriminative Learning for Unsupervised Domain Adaptation0
Domain Adaptive Transfer Learning with Specialist Models0
On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering0
Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective0
On Deep Domain Adaptation: Some Theoretical Understandings0
Unsupervised domain adaptation for medical imaging segmentation with self-ensemblingCode0
Domain Agnostic Real-Valued Specificity PredictionCode0
Co-regularized Alignment for Unsupervised Domain Adaptation0
Interactive dimensionality reduction using similarity projections0
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation0
Multiple Subspace Alignment Improves Domain Adaptation0
Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels0
Compact Personalized Models for Neural Machine Translation0
An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans.0
Show:102550
← PrevPage 109 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