SOTAVerified

Unsupervised Domain Adaptation

Unsupervised Domain Adaptation is a learning framework to transfer knowledge learned from source domains with a large number of annotated training examples to target domains with unlabeled data only.

Source: Domain-Specific Batch Normalization for Unsupervised Domain Adaptation

Papers

Showing 1251–1300 of 1951 papers

TitleStatusHype
Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition—0
Unsupervised Adaptive Semantic Segmentation with Local Lipschitz Constraint—0
Unsupervised Adversarial Domain Adaptation for Implicit Discourse Relation Classification—0
Unsupervised Adversarial Domain Adaptation For Barrett's Segmentation—0
Unsupervised Approach for Zero-Shot Experiments: Bhojpuri–Hindi and Magahi–Hindi@LoResMT 2020—0
Unsupervised Attention Regularization Based Domain Adaptation for Oracle Character Recognition—0
Unsupervised Class Generation to Expand Semantic Segmentation Datasets—0
Unsupervised Creation of Parameterized Avatars—0
Unsupervised Cross-Domain Soft Sensor Modelling via Deep Physics-Inspired Particle Flow Bayes—0
Unsupervised Deep Domain Adaptation for Pedestrian Detection—0
Unsupervised Disentanglement GAN for Domain Adaptive Person Re-Identification—0
Unsupervised Domain Adaptation across FMCW Radar Configurations Using Margin Disparity Discrepancy—0
Unsupervised Domain Adaptation: A Multi-task Learning-based Method—0
Unsupervised Domain Adaptation: A Reality Check—0
Unsupervised Domain Adaptation Based on Source-guided Discrepancy—0
Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition—0
Unsupervised domain adaptation by learning using privileged information—0
Unsupervised Domain Adaptation by Optical Flow Augmentation in Semantic Segmentation—0
Unsupervised Domain Adaptation By Optimal Transportation Of Clusters Between Domains—0
Unsupervised Domain Adaptation for Multispectral Pedestrian Detection—0
Unsupervised Domain Adaptation for Segmentation with Black-box Source Model—0
Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching—0
Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment—0
Unsupervised Domain Adaptation for Automated Knee Osteoarthritis Phenotype Classification—0
Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio—0
Unsupervised Domain Adaptation for Clinical Negation Detection—0
Unsupervised Domain Adaptation for COVID-19 Information Service with Contrastive Adversarial Domain Mixup—0
Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection—0
Unsupervised Domain Adaptation for Cross-Regional Scenes Person Re-identification—0
Unsupervised Domain Adaptation for RF-based Gesture Recognition—0
Unsupervised Domain Adaptation for Distance Metric Learning—0
Unsupervised Domain Adaptation for Dysarthric Speech Detection via Domain Adversarial Training and Mutual Information Minimization—0
Unsupervised Domain Adaptation for Event Detection using Domain-specific Adapters—0
Unsupervised Domain Adaptation for Event Detection via Meta Self-Paced Learning—0
Unsupervised Domain Adaptation for Extra Features in the Target Domain Using Optimal Transport—0
Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos—0
Graph Harmony: Denoising and Nuclear-Norm Wasserstein Adaptation for Enhanced Domain Transfer in Graph-Structured Data—0
Unsupervised Domain Adaptation for Hate Speech Detection Using a Data Augmentation Approach—0
Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning—0
Unsupervised Domain Adaptation for Joint Segmentation and POS-Tagging—0
Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach—0
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation—0
Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization—0
Unsupervised Domain Adaptation for Mobile Semantic Segmentation based on Cycle Consistency and Feature Alignment—0
Unsupervised Domain Adaptation for Monocular 3D Object Detection via Self-Training—0
Unsupervised Domain Adaptation for MRI Volume Segmentation and Classification Using Image-to-Image Translation—0
Unsupervised Domain Adaptation for Neuron Membrane Segmentation based on Structural Features—0
Unsupervised Domain Adaptation for Occlusion Resilient Human Pose Estimation—0
Unsupervised Domain Adaptation for One-stage Object Detector using Offsets to Bounding Box—0
Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CORE-ReIDmAP84.4—Unverified
2EvoADAmAP84.3—Unverified
3LF2mAP83.2—Unverified
4AWBmAP80.6—Unverified
5CCTSEmAP78.4—Unverified
6SpCLmAP76.7—Unverified
7MMTmAP71.2—Unverified
8SDAmAP70—Unverified
9AD-ClustermAP68.3—Unverified
10ECN++mAP63.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReIDmAP74.8—Unverified
2LF2mAP73.5—Unverified
3CCTSEmAP72.6—Unverified
4EvoADAmAP71.4—Unverified
5AWBmAP71—Unverified
6SpCLmAP68.8—Unverified
7MMTmAP65.1—Unverified
8SDAmAP61.4—Unverified
9SNRmAP58.1—Unverified
10ACTmAP54.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ALDI++(Resnet50+FPN)[email protected]66.8—Unverified
2RT-DATR(640x640, real-time)[email protected]52.7—Unverified
3MRT[email protected]51.2—Unverified
4DDT[email protected]50—Unverified
5MIC[email protected]47.6—Unverified
6O2net[email protected]46.8—Unverified
7LGCL (supervised)[email protected]46.7—Unverified
8LGCL (unsupervised)[email protected]45.3—Unverified
9SAD[email protected]45.2—Unverified
10ALDI-DETR (ResNet-50, 800px)[email protected]44.8—Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy91.4—Unverified
2TransAdapter-BAccuracy89.4—Unverified
3SAMBAccuracy86.2—Unverified
4PDA (CLIP, ViT-B/16)Accuracy85.7—Unverified
5SSRT-BAccuracy85.43—Unverified
6EUDAAccuracy84.9—Unverified
7ProDeAccuracy84.5—Unverified
8ECB (CNN)Accuracy81.2—Unverified
9CDTransAccuracy80.5—Unverified
10JAN [cite:ICML17JAN]Accuracy76.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReID V2mAP44.1—Unverified
2CORE-ReIDmAP41.9—Unverified
3CORE-ReID V2 TinymAP35.8—Unverified
4CCTSEmAP33.2—Unverified
5UMDAmAP32.7—Unverified
6AWBmAP30.6—Unverified
7SpClmAP25.4—Unverified
8SDAmAP23.2—Unverified
9MMTmAP22.9—Unverified
10DG-Net++mAP22.1—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 (baseline), BatchNorm Adaptation, 8 samplesmean Corruption Error (mCE)65—Unverified
2ResNet50 (baseline), BatchNorm Adaptation, full adaptationmean Corruption Error (mCE)62.2—Unverified
3ResNet50 + ENTmean Corruption Error (mCE)51.6—Unverified
4ResNet50 + RPLmean Corruption Error (mCE)50.5—Unverified
5ResNet50+DeepAug+AugMix, BatchNorm Adaptation, 8 samplesmean Corruption Error (mCE)48.4—Unverified
6ResNet50+DeepAug+AugMix, BatchNorm Adaptation, full adaptationmean Corruption Error (mCE)45.4—Unverified
7ResNeXt101 32x8d + ENTmean Corruption Error (mCE)44.3—Unverified
8ResNeXt101 32x8d + RPLmean Corruption Error (mCE)43.2—Unverified
9ResNeXt101 32x8d + IG-3.5B + RPLmean Corruption Error (mCE)40.9—Unverified
10ResNeXt101 32x8d + IG-3.5B + ENTmean Corruption Error (mCE)40.8—Unverified
#ModelMetricClaimedVerifiedStatus
1MIC+CSImIoU (13 classes)75.9—Unverified
2DCFmIoU (13 classes)75.9—Unverified
3DIDAmIoU (13 classes)70.1—Unverified
4Sepico + HIASTmIoU (13 classes)68.1—Unverified
5CLUDA+HRDAmIoU67.2—Unverified
6SePiCo (DeepLabv2 ResNet-101)mIoU (13 classes)66.5—Unverified
7G2LmIoU (13 classes)64.4—Unverified
8FAFSmIoU (13 classes)61.4—Unverified
9DAFormer+CSImIoU61.4—Unverified
10AdaptSeg + HIASTmIoU (13 classes)60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReID V2mAP49.5—Unverified
2MATNet+DMDUmAP49.25—Unverified
3MGR-GCLmAP48.73—Unverified
4PLMmAP47.37—Unverified
5CSP+FCDmAP45.6—Unverified
6PALmAP42.04—Unverified
7CORE-ReID V2 TinymAP40.17—Unverified
8SPCLmAP38.9—Unverified
9UDARmAP35.8—Unverified
10MMTmAP35.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReIDmAP45.2—Unverified
2CCTSEmAP34.5—Unverified
3AWBmAP30.7—Unverified
4SpCLmAP26.5—Unverified
5SDAmAP25.6—Unverified
6MMTmAP23.3—Unverified
7MMCLmAP16.2—Unverified
8ECN++mAP16—Unverified
9SSGmAP13.3—Unverified
10ECNmAP10.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ALDI++[email protected]77.8—Unverified
2ALDI-YOLO[email protected]75—Unverified
3MIC(ALDI frame)[email protected]73.1—Unverified
4AT(ALDI frame)[email protected]72—Unverified
5SADA(ALDI frame)[email protected]71.8—Unverified
6PT(ALDI frame)[email protected]70.6—Unverified
7RT-DATR(real-time, 640x640)[email protected]67.2—Unverified
8DDT[email protected]64—Unverified
9MRT[email protected]62—Unverified
10MILA[email protected]57.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReID V2mAP57.99—Unverified
2CORE-ReID V2 TinymAP55.14—Unverified
3DMDUmAP53.97—Unverified
4UDARmAP52.9—Unverified
5MGR-GCLmAP47.59—Unverified
6PMLmAP46—Unverified
7PALmAP45.14—Unverified
8MLmAP45—Unverified
9VDAFR-143.69—Unverified
10CSP+FCDmAP42.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CORE-ReID V2mAP63.02—Unverified
2CORE-ReID V2 TinymAP59.69—Unverified
3DMDUmAP56.73—Unverified
4UDARmAP55.3—Unverified
5MGR-GCLmAP50.56—Unverified
6PLMmAP49.41—Unverified
7MLmAP48.7—Unverified