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 49014950 of 6439 papers

TitleStatusHype
CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation0
CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseen0
Cross-domain Trajectory Prediction with CTP-Net0
CTS: Sim-to-Real Unsupervised Domain Adaptation on 3D Detection0
CUPR: Contrastive Unsupervised Learning for Person Re-identification0
Curriculum Guided Domain Adaptation in the Dark0
Curriculum Learning for Domain Adaptation in Neural Machine Translation0
Curriculum Learning for Few-Shot Domain Adaptation in CT-based Airway Tree Segmentation0
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation0
Curriculum Self-Paced Learning for Cross-Domain Object Detection0
Customizing Speech Recognition Model with Large Language Model Feedback0
CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation0
Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View0
Cycle-Consistent World Models for Domain Independent Latent Imagination0
Cycle Label-Consistent Networks for Unsupervised Domain Adaptation0
Cycle monotonicity of adversarial attacks for optimal domain adaptation0
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation0
DA^3:Dynamic Additive Attention Adaption for Memory-EfficientOn-Device Multi-Domain Learning0
DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptation0
DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception0
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection0
DAD: Data-free Adversarial Defense at Test Time0
DA-DETR: Domain Adaptive Detection Transformer with Information Fusion0
DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systems0
DAFD: Domain Adaptation via Feature Disentanglement for Image Classification0
GDA-HIN: A Generalized Domain Adaptive Model across Heterogeneous Information Networks0
DAIL: Dataset-Aware and Invariant Learning for Face Recognition0
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation0
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images0
Damage Control During Domain Adaptation for Transducer Based Automatic Speech Recognition0
DAMIA: Leveraging Domain Adaptation as a Defense against Membership Inference Attacks0
DAMix: A Density-Aware Mixup Augmentation for Single Image Dehazing under Domain Shift0
DAM-Net: Domain Adaptation Network with Micro-Labeled Fine-Tuning for Change Detection0
DaMSTF: Domain Adversarial Learning Enhanced Meta Self-Training for Domain Adaptation0
DandelionNet: Domain Composition with Instance Adaptive Classification for Domain Generalization0
DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains0
DANICE: Domain adaptation without forgetting in neural image compression0
DANNTe: a case study of a turbo-machinery sensor virtualization under domain shift0
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction0
DAPlankton: Benchmark Dataset for Multi-instrument Plankton Recognition via Fine-grained Domain Adaptation0
DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing0
DA-RAW: Domain Adaptive Object Detection for Real-World Adverse Weather Conditions0
DART^3: Leveraging Distance for Test Time Adaptation in Person Re-Identification0
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation0
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification0
DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout0
DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation0
DaSeGAN: Domain Adaptation for Segmentation Tasks via Generative Adversarial Networks0
DASGAN -- Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images0
Data Adaptation for Named Entity Recognition on Tweets with Features-Rich CRF0
Show:102550
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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