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 401–450 of 6439 papers

TitleStatusHype
Semi-Supervised Domain Adaptation with Source Label AdaptationCode1
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly DetectionCode1
Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic SegmentationCode1
Learning Data Representations with Joint Diffusion ModelsCode1
GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait RecognitionCode1
Adaptive Machine Translation with Large Language ModelsCode1
LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object DetectionCode1
Universal Domain Adaptation for Remote Sensing Image Scene ClassificationCode1
DEJA VU: Continual Model Generalization For Unseen DomainsCode1
Discriminator-free Unsupervised Domain Adaptation for Multi-label Image ClassificationCode1
Domain Adaptation for Head Pose Estimation Using Relative Pose ConsistencyCode1
MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation SegmentationCode1
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed ManipulationCode1
Adjustment and Alignment for Unbiased Open Set Domain AdaptationCode1
Weakly-Supervised Domain Adaptive Semantic Segmentation With Prototypical Contrastive LearningCode1
Towards Better Stability and Adaptability: Improve Online Self-Training for Model Adaptation in Semantic SegmentationCode1
CDAC: Cross-domain Attention Consistency in Transformer for Domain Adaptive Semantic SegmentationCode1
Single Domain Generalization for LiDAR Semantic SegmentationCode1
Dynamically Instance-Guided Adaptation: A Backward-Free Approach for Test-Time Domain Adaptive Semantic SegmentationCode1
Source-Free Adaptive Gaze Estimation by Uncertainty ReductionCode1
DARE-GRAM: Unsupervised Domain Adaptation Regression by Aligning Inverse Gram MatricesCode1
PODA: Prompt-driven Zero-shot Domain AdaptationCode1
Spacecraft Pose Estimation Based on Unsupervised Domain Adaptation and on a 3D-Guided Loss CombinationCode1
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth EstimationCode1
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation PipelineCode1
Cyclically Disentangled Feature Translation for Face Anti-spoofingCode1
3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic ViewsCode1
SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point CloudCode1
Union-set Multi-source Model Adaptation for Semantic SegmentationCode1
PØDA: Prompt-driven Zero-shot Domain AdaptationCode1
LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentationCode1
Towards Scene Understanding for Autonomous Operations on Airport ApronsCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
Zero-Shot Rumor Detection with Propagation Structure via Prompt LearningCode1
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive AlignmentCode1
CL3D: Unsupervised Domain Adaptation for Cross-LiDAR 3D DetectionCode1
Exploring Consistency in Cross-Domain Transformer for Domain Adaptive Semantic SegmentationCode1
DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple DomainsCode1
1st Place Solution to NeurIPS 2022 Challenge on Visual Domain AdaptationCode1
SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity RecognitionCode1
Unsupervised Continual Semantic Adaptation through Neural RenderingCode1
Object Detection in Foggy Scenes by Embedding Depth and Reconstruction into Domain AdaptationCode1
Sparse2Dense: Learning to Densify 3D Features for 3D Object DetectionCode1
FLAIR #1: semantic segmentation and domain adaptation datasetCode1
Anatomy-guided domain adaptation for 3D in-bed human pose estimationCode1
VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse ConditionsCode1
ProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image SegmentationCode1
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World SurveillanceCode1
Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive SurveyCode1
Robust Deep Learning for Autonomous DrivingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FFTATAverage Accuracy96—Unverified
2PMTransAverage Accuracy95.3—Unverified
3CMKDAverage Accuracy94.4—Unverified
4SSRT-B (ours)Average Accuracy93.5—Unverified
5CDTransAverage Accuracy92.6—Unverified
6CoViAverage Accuracy91.8—Unverified
7GSDEAverage Accuracy91.7—Unverified
8FixBiAverage Accuracy91.4—Unverified
9Contrastive Adaptation NetworkAverage Accuracy90.6—Unverified
10BIWAAAverage Accuracy90.5—Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU78.1—Unverified
2ILM-ASSLmIoU76.6—Unverified
3DCFmIoU69.3—Unverified
4HRDA+PiPamIoU68.2—Unverified
5MICmIoU67.3—Unverified
6FREDOM - TransformermIoU67—Unverified
7HRDAmIoU65.8—Unverified
8SePiComIoU64.3—Unverified
9MIC + Guidance TrainingmIoU63.8—Unverified
10DAFormer + ProCSTmIoU61.6—Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU77.8—Unverified
2DCFmIoU77.7—Unverified
3ILM-ASSLmIoU76.1—Unverified
4MICmIoU75.9—Unverified
5HRDA+PiPamIoU75.6—Unverified
6HRDAmIoU73.8—Unverified
7FREDOM - TransformermIoU73.6—Unverified
8HALOmIoU73.3—Unverified
9SePiComIoU70.3—Unverified
10DAFormer + ProCSTmIoU69.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SWGAccuracy92.3—Unverified
2RCLAccuracy90—Unverified
3PGA (ViT-L/14)Accuracy89.4—Unverified
4CMKDAccuracy89—Unverified
5PMTransAccuracy89—Unverified
6MICAccuracy86.2—Unverified
7PGA (ViT-B/16)Accuracy85.1—Unverified
8ELSAccuracy84.6—Unverified
9SDAT (ViT-B/16)Accuracy84.3—Unverified
10CDTrans (DeiT-B)Accuracy80.5—Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy93.8—Unverified
2RCLAccuracy93.2—Unverified
3MICAccuracy92.8—Unverified
4SWGAccuracy92.7—Unverified
5CMKDAccuracy91.8—Unverified
6DePTAccuracy90.7—Unverified
7SDAT(ViT)Accuracy89.8—Unverified
8SFDA2++Accuracy89.6—Unverified
9PMtransAccuracy88.8—Unverified
10CoViAccuracy88.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CMKDAccuracy94.3—Unverified
2MCC+NWDAccuracy90.7—Unverified
3GLOT-DRAccuracy90.4—Unverified
4SPLAccuracy90.3—Unverified
5DFA-SAFNAccuracy90.2—Unverified
6DADAAccuracy89.3—Unverified
7DFA-ENTAccuracy89.1—Unverified
8DDAAccuracy88.9—Unverified
9MEDMAccuracy88.9—Unverified
10IAFN+ENTAccuracy88.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SoRAmIoU78.8—Unverified
2ReinmIoU77.6—Unverified
3CoDAmIoU72.6—Unverified
4Refign (HRDA)mIoU72.1—Unverified
5HALOmIoU71.9—Unverified
6MICmIoU70.4—Unverified
7HRDAmIoU68—Unverified
8Refign (DAFormer)mIoU65.5—Unverified
9VBLC (DAFormer)mIoU64.2—Unverified
10CMFormermIoU60.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FACTAccuracy98.8—Unverified
2FAMCDAccuracy98.72—Unverified
3DFA-MCDAccuracy98.6—Unverified
4Mean teacherAccuracy98.26—Unverified
5DRANetAccuracy98.2—Unverified
6SHOTAccuracy98—Unverified
7DFA-ENTAccuracy97.9—Unverified
8CyCleGAN (Light-weight Calibrator)Accuracy97.1—Unverified