SOTAVerified

Multi-target Domain Adaptation

The idea of Multi-target Domain Adaptation is to adapt a model from a single labelled source domain to multiple unlabelled target domains.

Papers

Showing 1–10 of 39 papers

TitleStatusHype
ConvLoRA and AdaBN based Domain Adaptation via Self-TrainingCode2
Unsupervised Domain Adaptation by BackpropagationCode1
CoNMix for Source-free Single and Multi-target Domain AdaptationCode1
Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain TransferCode1
Cyclically Disentangled Feature Translation for Face Anti-spoofingCode1
Curriculum Graph Co-Teaching for Multi-Target Domain AdaptationCode1
A Multi Camera Unsupervised Domain Adaptation Pipeline for Object Detection in Cultural Sites through Adversarial Learning and Self-TrainingCode1
See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain AdaptationCode1
Cooperative Self-Training for Multi-Target Adaptive Semantic SegmentationCode1
Unsupervised Multi-Target Domain Adaptation Through Knowledge DistillationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MCDAAccuracy89.6—Unverified
2DCGCTAccuracy88.8—Unverified
3MT-MTDAAccuracy85.2—Unverified
4AMEANAccuracy80.2—Unverified
5RevGradAccuracy73.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MCDAAccuracy34.5—Unverified
2DCGCTAccuracy34.4—Unverified
3MCCAccuracy28.8—Unverified
4DADAAccuracy21.5—Unverified
#ModelMetricClaimedVerifiedStatus
1MCDAAccuracy71.1—Unverified
2DCGCTAccuracy69.8—Unverified
3AMEANAccuracy64—Unverified
4RevGradAccuracy57.9—Unverified
#ModelMetricClaimedVerifiedStatus
1STMDA-RetinaNet[email protected]66.64—Unverified