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SOTA
Domain Adaptation
Domain Adaptation On Office 31
Domain Adaptation On Office 31
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Average Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Average Accuracy
Paper Title
Repository
d-SNE
81.63
Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol
DAOD
85.4
Open Set Domain Adaptation: Theoretical Bound and Algorithm
MRKLD + LRENT
86.8
Confidence Regularized Self-Training
CMKD
94.4
Unsupervised Domain Adaption Harnessing Vision-Language Pre-training
DADA
89
Discriminative Adversarial Domain Adaptation
GTA
86.5
Generate To Adapt: Aligning Domains using Generative Adversarial Networks
PMTrans
95.3
Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective
-
CAADA
78.3
Correlation-aware Adversarial Domain Adaptation and Generalization
-
rRevGrad+CAT
80.1
Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
IDDA(Alexnet)
78.5
Looking back at Labels: A Class based Domain Adaptation Technique
SHOT
88.6
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
CDTrans
92.6
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
FixBi
91.4
FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation
BIWAA
90.5
Backprop Induced Feature Weighting for Adversarial Domain Adaptation with Iterative Label Distribution Alignment
SFDA2
89.9
SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
SRDA (RAN)
73.5
Learning Smooth Representation for Unsupervised Domain Adaptation
IDDA (AlexNet)
78.5
Looking back at Labels: A Class based Domain Adaptation Technique
dSNE
90.01
d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding
ELS
90.4
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
ResNet-50
76.1
Deep Residual Learning for Image Recognition
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