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 62016250 of 6439 papers

TitleStatusHype
Single-Shot Domain Adaptation via Target-Aware Generative AugmentationCode0
ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDACode0
Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-TrainingCode0
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing FlowsCode0
Overcoming Saturation in Density Ratio Estimation by Iterated RegularizationCode0
Cross-Domain Continual Learning via CLAMPCode0
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment ClassificationCode0
OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based CamerasCode0
Cross-Domain Conditional Diffusion Models for Time Series ImputationCode0
PAC-Bayesian Domain Adaptation Bounds for Multiclass LearnersCode0
Adaptor: Objective-Centric Adaptation Framework for Language ModelsCode0
Sketch Input Method Editor: A Comprehensive Dataset and Methodology for Systematic Input RecognitionCode0
Cross-Domain Complementary Learning Using Pose for Multi-Person Part SegmentationCode0
EIANet: A Novel Domain Adaptation Approach to Maximize Class Distinction with Neural Collapse PrinciplesCode0
Sliced Wasserstein Discrepancy for Unsupervised Domain AdaptationCode0
Efficient Pre-trained Features and Recurrent Pseudo-Labeling in Unsupervised Domain AdaptationCode0
PADA: Pruning Assisted Domain Adaptation for Self-Supervised Speech RepresentationsCode0
Sliced Wasserstein Discrepancy in Disentangling Representation and Adaptation Networks for Unsupervised Domain AdaptationCode0
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG SignalsCode0
Slicing the Gaussian Mixture Wasserstein DistanceCode0
Slimmable Domain AdaptationCode0
Efficient Machine Translation Domain AdaptationCode0
Towards Privacy-Supporting Fall Detection via Deep Unsupervised RGB2Depth AdaptationCode0
Towards Realistic Underwater Dataset Generation and Color RestorationCode0
Unsupervised Domain Adaptation by Uncertain Feature AlignmentCode0
Bootstrapping via Graph PropagationCode0
ADA-Net: Attention-Guided Domain Adaptation Network with Contrastive Learning for Standing Dead Tree Segmentation Using Aerial ImageryCode0
Unsupervised Domain Adaptation for Constraining Star Formation HistoriesCode0
Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label DiffusionCode0
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View ConsistencyCode0
SMILE: Sequence-to-Sequence Domain Adaption with Minimizing Latent Entropy for Text Image RecognitionCode0
Efficient k-Nearest-Neighbor Machine Translation with Dynamic RetrievalCode0
Efficient Cluster-Based k-Nearest-Neighbor Machine TranslationCode0
Supervised Domain Adaptation for Recognizing Retinal Diseases from Wide-Field Fundus ImagesCode0
Effective Unsupervised Domain Adaptation with Adversarially Trained Language ModelsCode0
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain AdaptationCode0
Unsupervised Graph Association for Person Re-IdentificationCode0
A Batch Normalization Classifier for Domain AdaptationCode0
Parameter Transfer Extreme Learning Machine based on Projective ModelCode0
Effective Pseudo-Labeling based on Heatmap for Unsupervised Domain Adaptation in Cell DetectionCode0
Pareto Domain AdaptationCode0
Boosting Novel Category Discovery Over Domains with Soft Contrastive Learning and All in One ClassifierCode0
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-LearningCode0
Unsupervised Domain Adaptation for Anatomical Landmark DetectionCode0
Boosting Domain Adaptation by Discovering Latent DomainsCode0
Soft Alignment Objectives for Robust Adaptation of Language GenerationCode0
Partial Adversarial Domain AdaptationCode0
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain AdaptationCode0
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature VectorsCode0
Solving Traffic4Cast Competition with U-Net and Temporal 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
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